U.S. patent application number 16/034098 was filed with the patent office on 2019-07-04 for vehicular image pickup device and image capturing method.
The applicant listed for this patent is GETAC TECHNOLOGY CORPORATION. Invention is credited to Kun-Yu TSAI.
Application Number | 20190202372 16/034098 |
Document ID | / |
Family ID | 67058606 |
Filed Date | 2019-07-04 |
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United States Patent
Application |
20190202372 |
Kind Code |
A1 |
TSAI; Kun-Yu |
July 4, 2019 |
VEHICULAR IMAGE PICKUP DEVICE AND IMAGE CAPTURING METHOD
Abstract
A vehicular image pickup device includes an image capturing unit
and a processing unit. The image capturing unit captures a
plurality of driving images sequentially. The driving images each
include an object image. The processing unit performs an image
analysis on two of the plurality of driving images to obtain a
variance of the object image and sets a shutter speed of the image
capturing unit according to the variance.
Inventors: |
TSAI; Kun-Yu; (Taipei City,
TW) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
GETAC TECHNOLOGY CORPORATION |
Hsinchu County |
|
TW |
|
|
Family ID: |
67058606 |
Appl. No.: |
16/034098 |
Filed: |
July 12, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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62613323 |
Jan 3, 2018 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04N 5/2354 20130101;
H04N 5/23229 20130101; B60R 11/04 20130101; H04N 5/243 20130101;
H04N 5/2353 20130101; H04N 5/2352 20130101; H04N 5/341 20130101;
G06T 7/97 20170101; H04N 5/2256 20130101 |
International
Class: |
B60R 11/04 20060101
B60R011/04; H04N 5/235 20060101 H04N005/235; H04N 5/232 20060101
H04N005/232; G06T 7/00 20060101 G06T007/00 |
Claims
1. An image capturing method, comprising the steps of: capturing a
plurality of driving images sequentially by an image capturing
unit, the driving images each comprising an object image;
performing an image analysis on two of the driving images to obtain
a variance of the object image; and setting a shutter speed of the
image capturing unit according to the variance.
2. The image capturing method of claim 1, wherein the step of
setting the shutter speed of the image capturing unit according to
the variance comprises: setting the shutter speed to one of a
plurality of predetermined shutter speed values according to the
variance if the variance is less than or equal to a variation
threshold; and setting the shutter speed to an initial shutter
speed value and fine-tuning a fill light intensity of a fill light
unit or a gain of the image capturing unit according to one of the
driving images if the variance is greater than the variation
threshold.
3. The image capturing method of claim 2, wherein the driving
images each comprise a plurality of pixels, and the step of
fine-tuning a fill light intensity of a fill light unit or a gain
of the image capturing unit according to one of the driving images
comprises: obtaining a grayscale quantity distribution of the
pixels of the driving images on a plurality of grayscale levels;
numbering the pixels sequentially in a direction from the highest
one of the grayscale levels to the lowest one of the grayscale
levels according to the grayscale quantity distribution until the
numbering reaches a predetermined number; and fine-tuning the fill
light intensity or the gain according to the grayscale level
associated with the pixels numbered with the predetermined
number.
4. The image capturing method of claim 3, wherein the grayscale
levels are divided into a first grayscale section, a second
grayscale section, a third grayscale section and a fourth grayscale
section sequentially in the direction from the highest grayscale
level to the lowest grayscale level, and the step of fine-tuning
the fill light intensity or the gain according to the grayscale
level associated with the pixels numbered with the predetermined
number comprises: decreasing the fill light intensity or the gain
if the grayscale level falls inside the first grayscale section;
not adjusting the fill light intensity or the gain if the grayscale
level falls inside the second grayscale section or the fourth
grayscale section; and increasing the fill light intensity or the
gain if the grayscale level falls inside the third grayscale
section.
5. The image capturing method of claim 2, wherein the step of
fine-tuning the fill light intensity or the gain according to one
of the driving images is followed by the steps of: calculating, by
conversion, a frequency spectrum in one of the driving images;
detecting a frequency domain location in the frequency spectrum;
and fine-tuning the gain or the fill light intensity and the
shutter speed according to whether any signal appears at the
frequency domain location.
6. The image capturing method of claim 5, wherein the step of
fine-tuning the gain or the fill light intensity and the shutter
speed comprises: not adjusting the gain or the fill light intensity
and the shutter speed if a signal appears at the frequency domain
location; and increasing the shutter speed and decreasing the fill
light intensity or the gain if no signal appears at the frequency
domain location.
7. The image capturing method of claim 5, wherein the frequency
domain location is obtained according to the number of pixels on a
straight line penetrating the driving images and the number of
pixels displaying a character image and aligned in the same
direction as the straight line.
8. The image capturing method of claim 2, wherein the step of
fine-tuning the fill light intensity or the gain according to one
of the driving images is followed by the steps of: retrieving the
object image from one of the driving images; calculating, by
conversion, a brightness distribution of the pixels on a straight
line penetrating the object image; and fine-tuning the gain and the
fill light intensity or the shutter speed according to a waveform
of the brightness distribution.
9. The image capturing method of claim 8, wherein the step of
fine-tuning the gain, the fill light intensity or the shutter speed
according to the waveform of the brightness distribution comprises:
comparing a peak-to-peak value of the waveform with a predetermined
difference; not adjusting the gain, the fill light intensity and
the shutter speed if the peak-to-peak value is greater than or
equal to the predetermined difference; and increasing the fill
light intensity or the gain if the peak-to-peak value is less than
the predetermined difference.
10. The image capturing method of claim 9, wherein the step of
fine-tuning the gain, the fill light intensity or the shutter speed
according to the waveform of the brightness distribution further
comprises: comparing a crest value of the waveform with a
predetermined peak value; not adjusting the gain, the fill light
intensity and the shutter speed if the crest value is greater than
or equal to the predetermined peak value; and increasing the fill
light intensity or the gain if the crest value is less than the
predetermined peak value
11. The image capturing method of claim 9, wherein the step of
fine-tuning the gain, the fill light intensity or the shutter speed
according to the waveform of the brightness distribution further
comprises: comparing a trough value of the waveform with a
predetermined trough value; decreasing the fill light intensity or
the gain if the trough value is greater than the predetermined
trough value; and not adjusting the gain, the fill light intensity
and the shutter speed if the trough value is less than or equal to
the predetermined trough value.
12. The image capturing method of claim 8, wherein the step of
fine-tuning the gain, the fill light intensity or the shutter speed
according to the waveform of the brightness distribution comprises:
not adjusting the gain, the fill light intensity and the shutter
speed if the number of grayscale pixels of each tangent of the
waveform is less than a predetermined number of grayscale pixels;
and increasing the shutter speed if the number of grayscale pixels
of any tangent of the waveform is greater than the predetermined
number of grayscale pixels.
13. The image capturing method of claim 5, wherein a product of the
shutter speed, the gain and the fill light intensity is
substantially the same before and after the fine-tuning.
14. A vehicular image pickup device, comprising: an image capturing
unit for capturing a plurality of driving images sequentially,
wherein the driving images each comprise an object image; and a
processing unit for performing an image analysis on two of the
driving images to obtain a variance of the object image and setting
a shutter speed of the image capturing unit according to the
variance.
15. The vehicular image pickup device of claim 14, further
comprising a fill light unit for providing a fill light of a fill
light intensity, wherein the processing unit sets the shutter speed
to one of a plurality of predetermined shutter speeds according to
the variance if the variance is less than or equal to a variation
threshold, sets the shutter speed to an initial shutter speed
value, and fine-tunes the fill light intensity or a gain of the
image capturing unit according to one of the driving images if the
variance is greater than the variation threshold.
16. The vehicular image pickup device of claim 15, wherein the
driving images each comprise a plurality of pixels, and the
processing unit further obtains a grayscale quantity distribution
of the pixels of the driving images on a plurality of grayscale
levels and numbers the pixels sequentially in a direction from the
highest one of the grayscale levels to the lowest one of the
grayscale levels according to the grayscale quantity distribution
until the numbering reaches a predetermined number, and the
processing unit fine-tunes the fill light intensity or the gain
according to the grayscale level associated with the pixels
numbered with the predetermined number.
17. The vehicular image pickup device of claim 16, wherein the
grayscale levels are divided into a first grayscale section, a
second grayscale section, a third grayscale section and a fourth
grayscale section sequentially in the direction from the highest
grayscale level to the lowest grayscale level, allowing the
processing unit to decrease the fill light intensity or the gain if
the grayscale level falls inside the first grayscale section,
causing the processing unit not to adjust the fill light intensity
or the gain if the grayscale level falls inside the second
grayscale section or the fourth grayscale section, and allowing the
processing unit to increase the fill light intensity or the gain if
the grayscale level falls inside the third grayscale section.
18. The vehicular image pickup device of claim 15, wherein, after
fine-tuning the fill light intensity or the gain according to one
of the driving images, the processing unit further calculates, by
conversion, a frequency spectrum in one of the driving images and
detects a frequency domain location in the frequency spectrum, and
the processing unit further fine-tunes the gain or the fill light
intensity and the shutter speed according to whether a signal
appears at the frequency domain location.
19. The vehicular image pickup device of claim 18, wherein the
processing unit does not adjust the gain or the fill light
intensity and the shutter speed if the signal appears at the
frequency domain location, and the processing unit increases the
shutter speed and decreases the fill light intensity or the gain if
the signal is absent from the frequency domain location.
20. The vehicular image pickup device of claim 18, wherein the
processing unit obtains the frequency domain location according to
the number of pixels on a straight line penetrating the driving
images and the number of pixels displaying a character image and
aligned in the same direction as the straight line.
21. The vehicular image pickup device of claim 15, wherein, after
fine-tuning the fill light intensity or the gain according to one
of the driving images, the processing unit further retrieves the
object image from one of the driving images to therefore calculate,
by conversion, a brightness distribution of the pixels on a
straight line penetrating the object image and fine-tune the gain,
the fill light intensity or the shutter speed according to a
waveform of the brightness distribution.
22. The vehicular image pickup device of claim 21, wherein the step
of fine-tuning the gain, the fill light intensity or the shutter
speed according to a waveform of the brightness distribution
comprises: comparing a peak-to-peak value of the waveform with a
predetermined difference; not adjusting the gain, the fill light
intensity and the shutter speed if the peak-to-peak value is
greater than or equal to the predetermined difference; and
increasing the fill light intensity or the gain if the peak-to-peak
value is less than the predetermined difference.
23. The vehicular image pickup device of claim 22, wherein the step
of fine-tuning the gain, the fill light intensity or the shutter
speed according to the waveform of the brightness distribution
further comprises: comparing a crest value of the waveform with a
predetermined peak value; not adjusting the gain, the fill light
intensity and the shutter speed if the crest value is greater than
or equal to the predetermined peak value; and increasing the fill
light intensity or the gain if the crest value is less than the
predetermined peak value.
24. The vehicular image pickup device of claim 22, wherein the step
of fine-tuning the gain, the fill light intensity or the shutter
speed according to the waveform of the brightness distribution
further comprises: comparing a trough value of the waveform with a
predetermined trough value; decreasing the fill light intensity or
the gain if the trough value is greater than the predetermined
trough value; and not adjusting the gain, the fill light intensity
and the shutter speed if the trough value is less than or equal to
the predetermined trough value.
25. The vehicular image pickup device of claim 21, wherein the
processing unit does not adjust the gain, the fill light intensity
and the shutter speed if the number of grayscale pixels of each
tangent of the waveform is less than a predetermined number of
grayscale pixels, and the processing unit increases the shutter
speed if the number of grayscale pixels of any tangent of the
waveform is greater than the predetermined number of grayscale
pixels.
26. The vehicular image pickup device of claim 18, wherein a
product of the shutter speed, the gain and the fill light intensity
is substantially the same before and after the fine-tuning.
Description
BACKGROUND OF THE INVENTION
Field of the Invention
[0001] The present disclosure relates to image capturing technology
and, more particularly, to a vehicular image pickup device and an
image capturing method.
Description of the Prior Art
[0002] Image pickup devices are capable of recording images and
thus have wide application, including ones installed at entrances
and exits of buildings which require surveillance, to assist with
tasks, such as conducting an investigation, preserving and
collecting evidence.
[0003] Normally, conventional image pickup devices are each
installed at a specific point to capture images within its image
capturing radius according to an invariable operation model.
However, if a conventional image pickup device is mounted on a
moving object, for example, a vehicle, image quality of images
captured by the image pickup device deteriorates, depending on the
speed of the moving object. Furthermore, accuracy of ensuing
recognition of the captured images is affected.
SUMMARY OF THE INVENTION
[0004] In an embodiment, an image capturing method comprises the
steps of: capturing a plurality of driving images sequentially by
an image capturing unit; performing an image analysis on two of the
driving images to obtain a variance of the object image; and
setting a shutter speed of the image capturing unit according to
the variance. The driving images each comprise an object image.
[0005] In an embodiment, a vehicular image pickup device comprises
an image capturing unit and a processing unit. The image capturing
unit captures a plurality of driving images sequentially. The
driving images each comprise an object image. The processing unit
performs an image analysis on two of the driving images to obtain a
variance of the object image. Then, the processing unit sets a
shutter speed of the image capturing unit according to the
variance.
[0006] In conclusion, a vehicular image pickup device and an image
capturing method in the embodiments of the present disclosure set a
shutter speed according to a variance of an object image in driving
images so as to obtain sharp driving images, fine-tune a fill light
intensity or gain according to a grayscale quantity distribution of
the driving images so as to obtain driving images with appropriate
brightness, and fine-tune the shutter speed, fill light intensity
or gain according to a frequency spectrum of the driving images or
a brightness distribution of an object image so as to augment the
detailed performance of the driving images. Furthermore, the
vehicular image pickup device and the image capturing method in the
embodiments of the present disclosure dispense with the need to
wait for feedback from a back-end system and thus are capable of
confirming the image quality of the driving images and performing
fine-tuning operation; hence, the driving images of enhanced image
quality can be quickly obtained.
[0007] Fine structures and advantages of the present disclosure are
described below with reference to preferred embodiments of the
present disclosure to enable persons skilled in the art to gain
insight into the technical features of the present disclosure and
implement the present disclosure accordingly. Persons skilled in
the art can easily understand the objectives and advantages of the
present disclosure by making reference to the disclosure contained
in the specification, the claims, and the drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] FIG. 1 is a block diagram of a vehicular image pickup device
according to an embodiment of the present disclosure;
[0009] FIG. 2 is a schematic view of a process flow of an image
capturing method according to an embodiment of the present
disclosure;
[0010] FIG. 3 is a schematic view of a process flow of step S30 in
FIG. 2 according to an embodiment of the present disclosure;
[0011] FIG. 4 is a schematic view of a process flow of step S34 in
FIG. 3 according to an embodiment of the present disclosure;
[0012] FIG. 5 is a histogram of driving images according to an
embodiment of the present disclosure;
[0013] FIG. 6 is a schematic view of a process flow of step S34C in
FIG. 4 according to an embodiment of the present disclosure;
[0014] FIG. 7 is a schematic view of a process flow of an image
capturing method after step S34 according to an embodiment of the
present disclosure;
[0015] FIG. 8 is a schematic view of driving images according to an
embodiment of the present disclosure;
[0016] FIG. 9 is a schematic view of a process flow of step S37 in
FIG. 7 according to an embodiment of the present disclosure;
[0017] FIG. 10 is a schematic view of a process flow of an image
capturing method after step S34 according to an embodiment of the
present disclosure;
[0018] FIG. 11 is a schematic view of an object image and its
brightness distribution according to an embodiment of the present
disclosure;
[0019] FIG. 12 is a schematic view of a process flow of step S40 in
FIG. 10 according to an embodiment of the present disclosure;
[0020] FIG. 13 is a schematic view of a process flow of step S40 in
FIG. 10 according to an embodiment of the present disclosure;
[0021] FIG. 14 is a schematic view of a process flow of step S40 in
FIG. 10 according to an embodiment of the present disclosure;
[0022] FIG. 15 is a schematic view of a process flow of step S40 in
FIG. 10 according to an embodiment of the present disclosure;
[0023] FIG. 16 is a schematic view of a process flow of step S40 in
FIG. 10 according to an embodiment of the present disclosure;
[0024] FIG. 17 is a schematic view of a process flow of step S40 in
FIG. 10 according to an embodiment of the present disclosure;
[0025] FIG. 18 is a schematic view of an object image and its
brightness distribution according to an embodiment of the present
disclosure; and
[0026] FIG. 19 is a schematic view of the object image and its
brightness distribution according to an embodiment of the present
disclosure.
DETAILED DESCRIPTION OF THE EMBODIMENTS
[0027] FIG. 1 is a block diagram of a vehicular image pickup device
100 according to an embodiment of the present disclosure. Referring
to FIG. 1, in general, the vehicular image pickup device 100 is
mounted on a means of transport and adapted to capture and record a
driving image F1. In some embodiment aspects, the means of
transport is a car or a motorcycle, but the present disclosure is
not limited thereto. Any appropriate means of transport, which is
suitable for use with the vehicular image pickup device 100, is
applicable to the present disclosure.
[0028] In an embodiment, the vehicular image pickup device 100
comprises an image capturing unit 110 and a processing unit 120.
The processing unit 120 is coupled to the image capturing unit 110.
The vehicular image pickup device 100 further comprises a fill
light unit 130. The fill light unit 130 is coupled to the image
capturing unit 110 and the processing unit 120.
[0029] The image capturing unit 110 captures a plurality of driving
images F1. The driving images F1 are frames captured by the image
capturing unit 110 during a continuous time period. The fill light
unit 130 outputs a fill light, i.e., a supplementary light, so as
to assist with the image-capturing function of the image capturing
unit 110.
[0030] In some embodiment aspects, the image capturing unit 110
comprises an assembly of lenses and light-sensing components. The
light-sensing components include, for example, a complementary
metal-oxide semiconductor (CMOS) and a charge-coupled device (CCD).
The fill light unit 130 is, for example, implemented by a
light-emitting diode (LED), an infrared LED (IR LED), a halogen
lamp, or a laser source, but the present disclosure is not limited
thereto.
[0031] The processing unit 120 controls and adjusts the operation
of the image capturing unit 110 and/or the fill light unit 130
according to the image capturing method in any embodiment of the
present disclosure to enhance the image quality of the driving
images F1 captured by the image capturing unit 110.
[0032] In some embodiment aspects, the processing unit 120 is, for
example, a system-on-a-chip (SoC), a central processing unit (CPU),
a microcontroller (MCU), or an application-specific integrated
circuit (ASIC).
[0033] FIG. 2 is a schematic view of a process flow of an image
capturing method according to an embodiment of the present
disclosure. Referring to FIG. 1 and FIG. 2, using an embodiment of
the image capturing method, the processing unit 120 instructs the
image capturing unit 110 to capture a plurality of driving images
F1 sequentially (step S10). The driving images F1 each comprise an
object image M1. Afterward, the processing unit 120 performs an
image analysis on two of the driving images F1 to obtain a variance
of the object image M1 in the two driving images F1 (step S20).
Then, the processing unit 120 sets a shutter speed of the image
capturing unit 110 according to the variance obtained in step S20
(step S30). Afterward, the processing unit 120 goes back to step
S10 to repeat the aforesaid adjustment steps again.
[0034] In an embodiment of step S10, the image capturing unit 110
captures each driving image F1 with a global shutter, but the
present disclosure is not limited thereto. In a variant embodiment
of step S10, the image capturing unit 110 captures each driving
image F1 with a rolling shutter.
[0035] In an initial state, the image capturing unit 110 captures a
plurality of driving images F1 sequentially at a predetermined
shutter speed. In some embodiment aspects, the predetermined
shutter speed ranges from 1/1000 to 1/100000 per second.
[0036] In an embodiment of step S20, the processing unit 120
performs an image processing process on each driving image F1 to
confirm whether the driving images F1 each include the object image
M1.
[0037] In an embodiment of step S20, the processing unit 120
performs an image analysis on any two of the driving images F1
selectively, as long as the two selected driving images F1 include
the object image M1, so as to obtain a variance. In an embodiment
aspect, the processing unit 120 selectively performs an image
analysis on both the first one of the driving images F1 (if the
first one of the driving images F1 includes the object image M1)
and the last one of the driving images F1 (if the last one of the
driving images F1 includes the object image M1.) In another
embodiment aspect, the processing unit 120 selectively performs an
image analysis on two consecutive ones of the driving images F1, as
long as the two consecutive driving images F1 include the object
image M1. The variance obtained as a result of the image analysis
performed by the processing unit 120 is the displacement (i.e.,
variation in location) of the object image M1 in the two driving
images F1; hence, the variance is location variance, for example,
the distance traveled by the object image M1 along the X-axis in
the two driving images F1, but the present disclosure is not
limited thereto. In a variant embodiment, the variance obtained by
the processing unit 120 is the speed at which the object image M1
moves as shown in the two driving images F1.
[0038] In some embodiment aspects, the processing unit 120 obtains
the variance of the object image M1 by image subtraction, but the
present disclosure is not limited thereto. In a variant embodiment,
the processing unit 120 obtains the variance of the object image M1
by any appropriate image analysis algorithm.
[0039] FIG. 3 is a schematic view of a process flow of step S30 in
FIG. 2 according to an embodiment of the present disclosure. In an
embodiment of step S30, the processing unit 120 compares the
variance of the object image M1 with a predetermined variation
threshold (step S31). Upon determination that the variance is less
than or equal to the variation threshold, the processing unit 120
selects a predetermined shutter speed value from a plurality of
predetermined shutter speed values according to the current value
of the variance and sets the shutter speed of the image capturing
unit 110 to the predetermined shutter speed value (step S32). Upon
determination that the variance is greater than the variation
threshold, the processing unit 120 sets the shutter speed of the
image capturing unit 110 to an initial shutter speed value (step
S33) and then fine-tunes the fill light intensity of the fill light
unit 130 or the gain of the image capturing unit 110 according to
one of the driving images F1 (step S34).
[0040] In some embodiments, the vehicular image pickup device 100
further comprises a storage unit 140. The storage unit 140 is
coupled to the processing unit 120. The storage unit 140 stores the
variation threshold, the predetermined shutter speed values, the
initial shutter speed value, the fill light intensity and/or
gain.
[0041] In an embodiment of step S32, an exemplary relationship
between the variance value and the predetermined shutter speed
value is shown in Table 1. For the sake of illustration, Table 1
shows only four variance values and their respective predetermined
shutter speed values. As shown in Table 1, the variance relates to
speed, and its unit of measurement is km/h, whereas the unit of
measurement of the predetermined shutter speed values is second,
but the present disclosure is not limited thereto.
TABLE-US-00001 TABLE 1 relationship between predetermined shutter
speed value and variance value Serial number A1 A2 A3 A4 Variance
value 20 40 80 160 Predetermined 1/500 1/1000 1/2000 1/4000 shutter
speed value
[0042] Referring to Table 1, variances A1-A4 each have a one-to-one
relationship with its respective predetermined shutter speed value
substantially, and their relationships are stored in the storage
unit 140. Therefore, in step S32, the processing unit 120 selects
the predetermined shutter speed values by looking up the table.
[0043] For instance, given a variation threshold of 40 (km/h), if
the variance obtained by the processing unit 120 is 20 (km/h) and
thus less than the variation threshold, the processing unit 120
compares the obtained variance with the variances A1-A4 shown in
Table 1 descriptive of the aforesaid relationships stored in the
storage unit 140. Therefore, if the variance obtained by the
processing unit 120 equals variance A1, the processing unit 120
identifies the predetermined shutter speed value to be 1/500
(second) according to Table 1 and sets the shutter speed of the
image capturing unit 110 accordingly. In another embodiment, if the
variance obtained by the processing unit 120 is 30 (km/h) and thus
less than the variation threshold, the processing unit 120 compares
the obtained variance with the variances A1-A4 shown in Table 1
descriptive of the aforesaid relationships stored in the storage
unit 140. However, none of the variances obtained by the processing
unit 120 equals the variances A1-A4, and thus the processing unit
120 sets the shutter speed of the image capturing unit 110 with
variance A2 which is greater than and closest to the obtained
variances.
[0044] In an embodiment of step S33, the initial shutter speed
value is 1/1000 second.
[0045] In an embodiment of step S34, the driving image F1 comprises
a plurality of pixels. The pixels display grayscales according to
grayscale levels in a plurality of grayscale levels. Hence, how the
driving image F1 looks depends on the grayscales displayed by the
pixels and their locations.
[0046] In some embodiment aspects, the driving image F1 consists of
1280*720 pixels, but the present disclosure is not limited thereto.
In a variant embodiment, the driving image F1 consists of 360*240
pixels, 1920*1080 pixels, or any display standard-complying number
of pixels.
[0047] In some embodiment aspects, the grayscale levels are in the
number of 256, for example, from grayscale level 0 to grayscale
level 255, with grayscale level 0 denoting the least brightness,
and grayscale level 255 denoting the highest brightness, but the
present disclosure is not limited thereto. In a variant embodiment,
the number of the grayscale levels depends on the performance of
the image capturing unit 110. For instance, the image capturing
unit 110 comprises an analog-to-digital conversion circuit. If the
analog-to-digital conversion circuit operates on a 10-bit basis,
the image capturing unit 110 provides performance of 1024 (i.e.,
2.sup.10) grayscale levels. The other cases are inferred by
analogy.
[0048] FIG. 4 is a schematic view of a process flow of step S34 in
FIG. 3 according to an embodiment of the present disclosure. FIG. 5
is a histogram of driving images according to an embodiment of the
present disclosure. Referring to FIG. 1 through FIG. 5, in an
embodiment of step S34, the processing unit 120 makes a histogram
of the driving images F1 by image integration and thus obtains a
grayscale quantity distribution of the pixels of the driving images
F1 on a plurality of grayscale levels (step S34A). Then, the
processing unit 120 numbers the pixels sequentially in the
direction from the highest grayscale level to the lowest grayscale
level according to the grayscale quantity distribution obtained in
step S34A until the numbering reaches a predetermined number (step
S34B). Afterward, the processing unit 120 fine-tunes the fill light
intensity of the fill light unit 130 or the gain of the image
capturing unit 110 according to the grayscale level of the pixel
whose number is the predetermined number (step S34C) such that the
highest brightness of the driving images F1 can be adjusted to a
reasonable range without becoming too bright or too dim.
[0049] In an embodiment of step S34B, the predetermined number
equals the number of pixels generally occupied by the object image
M1 in the driving images F1. In some embodiment aspects, if the
object image M1 is an image of a license plate, the predetermined
number ranges from 1000 to 3000 or ranges from 2000 to 3000, but
the present disclosure is not limited thereto. In a variant
embodiment, the predetermined number depends on the number of
pixels which must be occupied by the image of the license plate in
order to correctly recognize every country's license plates and
sizes thereof.
[0050] In general, the object image M1 in the driving images F1
captured in the presence of the fill light of the fill light unit
130 must has the highest brightness, when compared with the rest of
the driving images F1, hence, the pixels displaying the object
image M1 must be associated with the relatively high grayscale
levels in the grayscale quantity distribution. Therefore, the
processing unit 120 numbers the pixels sequentially in the
direction from the highest grayscale level to the lowest grayscale
level so as to identify the lowest grayscale level associated with
the pixels displaying the object image M1.
[0051] For instance, given 256 grayscale levels and a predetermined
number 1000, the processing unit 120 numbers pixels sequentially in
the direction from grayscale level 255 to grayscale level 0, that
is, numbers the pixels at grayscale level 255, the pixels at
grayscale level 254, the pixels at grayscale level 253, and so
forth. The aforesaid pixel numbering process is accompanied by the
cumulative counting of the pixels numbered, and it stops as soon as
the count reaches the predetermined number 1000.
[0052] FIG. 6 is a schematic view of a process flow of step S34C in
FIG. 4 according to an embodiment of the present disclosure.
Referring to FIG. 1 through FIG. 6, in an embodiment of step S34C,
the grayscale levels are divided into a plurality of grayscale
sections. The processing unit 120 performs adjustment operations by
identifying the grayscale section which the grayscale level
associated with the pixels numbered with the predetermined number
falls inside.
[0053] The description below is exemplified by 256 grayscale
levels. The grayscale levels are divided into grayscale sections,
namely the first grayscale section, the second grayscale section,
the third grayscale section and the fourth grayscale section,
sequentially in the direction from the highest grayscale level 255
to the lowest grayscale level 0. The grayscale level 255 to
grayscale level 200 are defined as the first grayscale section. The
grayscale level 199 to grayscale level 150 are defined as the
second grayscale section. The grayscale level 149 to grayscale
level 100 are defined as the third grayscale section. The grayscale
level 99 to grayscale level 0 are defined as the fourth grayscale
section. The exemplary relationship between the grayscale sections
and adjustment operations are shown in Table 2 below.
TABLE-US-00002 TABLE 2 relationship between grayscale sections and
adjustment operations Grayscale section First Second Third Fourth
grayscale grayscale grayscale grayscale section section section
section Grayscale 255~200 199~150 149~100 99~0 level Brightness Too
bright Appropriate Too dim No object status image Adjustment
Decrease fill Nil Increase fill Nil operation light intensity light
intensity or gain or gain
[0054] If the grayscale level associated with the pixels numbered
with the predetermined number falls inside the first grayscale
section, it means that the object image M1 is currently too bright.
Therefore, the processing unit 120 decrease the fill light
intensity of the fill light unit 130 or the gain of the image
capturing unit 110 (step S34C1) in order to correct the
problem.
[0055] If the grayscale level associated with the pixels numbered
with the predetermined number falls inside the second grayscale
section, it means that brightness of the object image M1 is
currently appropriate. Therefore, the processing unit 120 does not
adjust the fill light intensity of the fill light unit 130 or the
gain of the image capturing unit 110 (step S34C2).
[0056] If the grayscale level associated with the pixels numbered
with the predetermined number falls inside the third grayscale
section, it means that the object image M1 is currently too dim.
Therefore, the processing unit 120 increases the fill light
intensity of the fill light unit 130 or the gain of the image
capturing unit 110 (step S34C3) in order to correct the
problem.
[0057] If the grayscale level associated with the pixels numbered
with the predetermined number falls inside the fourth grayscale
section, it means that the object image M1 is absent from the
driving images F1. Therefore, the processing unit 120 does not
perform any adjustment operation but proceeds to perform step
S34C2.
[0058] FIG. 7 is a schematic view of a process flow of an image
capturing method after step S34 according to an embodiment of the
present disclosure. FIG. 8 is a schematic view of driving images
according to an embodiment of the present disclosure. Referring to
FIG. 1 through FIG. 8, in an embodiment of the image capturing
method, after step S34, the processing unit 120 performs frequency
domain conversion on one of the driving images F1 to calculate, by
conversion, a frequency spectrum of the driving image F1 (step
S35). Afterward, the processing unit 120 further detects a
frequency domain location in the frequency spectrum (step S36),
fine-tunes the fill light intensity of the fill light unit 130 or
the gain of the image capturing unit 110, and fine-tunes the
shutter speed of the image capturing unit 110, according to whether
any signal appears at the frequency domain location (step S37), so
as to further optimize the image quality of the images captured by
the vehicular image pickup device 100 by the aforesaid fine-tuning
operations.
[0059] In an embodiment of step S35, the frequency domain
conversion is implemented by Fourier transform.
[0060] In an embodiment of step S36, the object image M1 comprises
a plurality of character images W1. The processing unit 120 defines
a straight line L1 penetrating the driving images F1 and thus
obtains the frequency domain location according to the number of
pixels on the straight line L1 penetrating the driving images F1
and the number of pixels displaying the character images W1 and
aligned in the same direction as the straight line L1. In some
embodiment aspects, the frequency domain location is a high
frequency location in the frequency spectrum.
[0061] The description below is exemplified by the driving image F1
with an image format of 1280*720. If the driving image F1 has an
image format of 1280*720, it means that the driving image F1 has
1280 pixels on the horizontal axis (i.e., X-axis) and 720 pixels on
the vertical axis (i.e., Y-axis), and thus the driving image F1
consists of 1280*720 pixels. If the processing unit 120 defines the
straight line L1 which runs along the horizontal axis of the
driving image F1, the straight line L1 must penetrate 1280 pixels
in the driving image F1. The number of pixels (along the straight
line L1) displaying the character images W1 equals the number (say,
3.about.10) of pixels required for recognition of the character
images W1. In this regard, the description below is exemplified by
three pixels. Therefore, the processing unit 120 detects 3/1280
frequency domain locations, but the present disclosure is not
limited thereto. In a variant embodiment, the straight line L1
penetrating the driving image F1 runs along the vertical axis of
the driving image F1 or in any other appropriate direction.
[0062] FIG. 9 is a schematic view of a process flow of step S37 in
FIG. 7 according to an embodiment of the present disclosure.
Referring to FIG. 1 through FIG. 9, in an embodiment of step S37,
if in step S36 the processing unit 120 detects that a signal
appears at the frequency domain location, the processing unit 120
determines that the driving image F1 is sharp enough, and thus the
processing unit 120 does not adjust the gain and shutter speed of
the image capturing unit 110 and the fill light intensity of the
fill light unit 130 (step S37A). If in step S36 the processing unit
120 does not detect any signal at the frequency domain location,
the processing unit 120 determines that the driving image F1 is not
sharp enough, that is, is blurred, and thus the processing unit 120
increases the shutter speed of the image capturing unit 110 and
decreases one of the gain of the image capturing unit 110 and the
fill light intensity of the fill light unit 130 (step S37B), so as
to ensure that the driving images F1 captured by the image
capturing unit 110 after the fine-tuning operations will have
sufficient brightness and sharpness.
[0063] In some embodiments, the processing unit 120 performs step
S35 through step S37 repeatedly to effectuate fine-tuning
repeatedly, and it is only when the processing unit 120 determines
that the driving image F1 has sufficiently high spectrum response
that the processing unit 120 stops performing the fine-tuning
operations of step S35 through step S37.
[0064] In conclusion, in step S35 through step S37, the processing
unit 120 confirms whether the driving image F1 lacks a high
frequency signal by frequency domain conversion and thus confirms
the image quality of the driving image F1 to therefore enable quick
feedback and perform fine-tuning accordingly, so as to obtain the
driving images F1 with enhanced image quality quickly.
[0065] FIG. 10 is a schematic view of a process flow of an image
capturing method after step S34 according to an embodiment of the
present disclosure. FIG. 11 is a schematic view of an object image
and its brightness distribution according to an embodiment of the
present disclosure. Referring to FIG. 10 and FIG. 11, in an
embodiment of the image capturing method, after step S34, the
processing unit 120 retrieves the object image M1 from one of the
driving images F1 (step S38) to therefore calculate, by conversion,
a brightness distribution of the pixels on a straight line L2
penetrating the object image M1 (step S39). Afterward, the
processing unit 120 fine-tunes the gain of the image capturing unit
110, the fill light intensity of the fill light unit 130 or the
shutter speed of the image capturing unit 110 according to a
waveform of the brightness distribution (step S40), so as to
optimize the image quality of images captured by the vehicular
image pickup device 100 by the aforesaid fine-tuning
operations.
[0066] In some embodiments, the processing unit 120 performs step
S38 through step S40 repeatedly to effectuate fine-tuning
repeatedly, and it is only when the processing unit 120 determines
that the driving image F1 has sufficiently high image quality that
the processing unit 120 stops performing the fine-tuning operations
of step S38 through step S40.
[0067] In an embodiment of step S38, the processing unit 120
retrieves the object image M1 from the driving image F1 by image
processing technology, for example, image division.
[0068] In an embodiment of step S39, the processing unit 120
defines a straight line L2 penetrating the object image M1 and thus
calculates, by conversion, a brightness distribution of brightness
against location, according to all the pixels on the straight line
L2 and their locations. In some embodiment aspects, the processing
unit 120 defines the straight line L2 along the horizontal axis of
the object image M1, but the present disclosure is not limited
thereto. In a variant embodiment, the straight line L2 penetrating
the object image M1 runs along the vertical axis of the object
image M1 or in any other appropriate direction. In this regard, the
object image M1 comprises a plurality of character images W1, and
the straight line L2 penetrates character images W1.
[0069] FIG. 12 is a schematic view of a process flow of step S40 in
FIG. 10 according to an embodiment of the present disclosure.
Referring to FIG. 10 through FIG. 12, in an embodiment of step S40,
the processing unit 120 performs the fine-tuning step according to
a peak-to-peak value Vpp of the waveform of the brightness
distribution calculated in step S39. The peak-to-peak value Vpp
equals the difference between crest Vc and trough Vt of the
waveform of the brightness distribution. Therefore, the processing
unit 120 compares peak-to-peak value Vpp of the waveform with a
predetermined difference (step S41). If the peak-to-peak value Vpp
is greater than or equal to the predetermined difference, the
processing unit 120 determines that the contrast of the object
image M1 is sufficient and thus does not adjust the gain of the
image capturing unit 110, the fill light intensity of the fill
light unit 130, and the shutter speed of the image capturing unit
110 (step S42). If the peak-to-peak value Vpp is less than the
predetermined difference, the processing unit 120 determines that
contrast of the object image M1 is insufficient and enables the
fill light unit 130 to increase its fill light intensity or enables
the image capturing unit 110 to increase its gain (step S43), so as
to increase the contrast of the object image M1 in the driving
image F1 captured after the fine-tuning step.
[0070] In some embodiment aspects, the unit of measurement of the
brightness in the brightness distribution is a grayscale level. The
predetermined difference ranges from 90 grayscale levels to 110
grayscale levels. For instance, the predetermined difference is 100
grayscale levels, but the present disclosure is not limited
thereto.
[0071] FIG. 13 is a schematic view of a process flow of step S40 in
FIG. 10 according to an embodiment of the present disclosure.
Referring to FIG. 13, in an embodiment of step S40, in addition to
the peak-to-peak value Vpp, the processing unit 120 performs
fine-tuning according to a crest value. In an embodiment aspect,
after step S41 and determining that the peak-to-peak value Vpp is
greater than or equal to the predetermined difference, the
processing unit 120 compares a crest value of the waveform with a
predetermined peak value (step S44). If the comparison carried out
in step S44 shows that the crest value is greater than or equal to
the predetermined peak value, it means that the object image M1
does not have overly low brightness (i.e., is not too dim), and
thus the processing unit 120 proceeds to perform step S42, that is,
the processing unit 120 does not perform adjustment. Conversely, if
the comparison carried out in step S44 shows that the crest value
is less than the predetermined peak value, it means that the object
image M1 is likely to have overly low brightness (i.e., is likely
to be too dim), and thus the processing unit 120 performs step S43
in order to increase the brightness of the object image M1, but the
present disclosure is not limited thereto. FIG. 14 is a schematic
view of a process flow of step S40 in FIG. 10 according to an
embodiment of the present disclosure. Referring to FIG. 14, in
another embodiment aspect, the processing unit 120 performs step
S44 before step S41. Afterward, if the comparison carried out in
step S44 shows that the crest value is greater than or equal to
predetermined peak value, the processing unit 120 proceeds to
perform step S41 which entails comparing the peak-to-peak value Vpp
and the predetermined difference. Then, the processing unit 120
proceeds to perform step S42 or step S43 according to the
comparison result of step S41. If the comparison carried out in
step S44 shows that the crest value is less than the predetermined
peak value, the processing unit 120 proceeds to perform step
S43.
[0072] FIG. 15 is a schematic view of a process flow of step S40 in
FIG. 10 according to an embodiment of the present disclosure.
Referring to FIG. 15, in an embodiment of step S40, in addition to
the peak-to-peak value, the processing unit 120 performs
fine-tuning according to a trough value. In an embodiment aspect,
after step S41 and determining that the peak-to-peak value is
greater than or equal to the predetermined difference, the
processing unit 120 compares the trough value of the waveform with
a predetermined trough value (step S45). If the comparison carried
out in step S45 shows that the trough value is less than or equal
to the predetermined trough value, it means that the object image
M1 does not have overly high brightness (i.e., is not too bright),
the processing unit 120 proceeds to perform step S42 (i.e., does
not perform adjustment). Conversely, if the comparison carried out
in step S45 shows that the trough value is greater than the
predetermined trough value, it means: the object image M1 is likely
to have overly high brightness (i.e., is likely to be too bright);
the processing unit 120 enables the fill light unit 130 to decrease
its fill light intensity or enables the image capturing unit 110 to
decrease its gain (step S46), but the present disclosure is not
limited thereto. FIG. 16 is a schematic view of a process flow of
step S40 in FIG. 10 according to an embodiment of the present
disclosure. Referring to FIG. 16, in another embodiment aspect, the
processing unit 120 performs step S45 before step S41. Afterward,
if the comparison carried out in step S45 shows that the trough
value is less than or equal to the predetermined trough value, the
processing unit 120 proceeds to perform step S41 which entails
comparing the peak-to-peak value Vpp and the predetermined
difference. Then, the processing unit 120 proceeds to perform step
S42 or step S43 according to the comparison result of step S41. If
the comparison carried out in step S45 shows that the trough value
is greater than the predetermined trough value, the processing unit
120 proceeds to perform step S46.
[0073] In some embodiment aspects, predetermined peak value ranges
from grayscale level 120 to grayscale level 140. The predetermined
trough value ranges from grayscale level 120 to grayscale level
140. In some embodiment aspects, the predetermined peak value
equals the predetermined trough value. For example, both the
predetermined peak value and the predetermined trough value are
grayscale level 130, but the present disclosure is not limited
thereto.
[0074] FIG. 17 is a schematic view of a process flow of step S40 in
FIG. 10 according to an embodiment of the present disclosure. FIG.
18 is a schematic view of an object image and its brightness
distribution according to an embodiment of the present disclosure.
FIG. 19 is a schematic view of the object image and its brightness
distribution according to an embodiment of the present disclosure.
Referring to FIG. 10, FIG. 17 through FIG. 19, in an embodiment of
step S40, the processing unit 120 performs the fine-tuning step
according to the number of grayscale pixels of each tangent Lt of
the waveform of the brightness distribution calculated in step S39.
The number of grayscale pixels of each tangent Lt equals the
transition slope in transiting from crest Vc to trough Vt or the
transition slope in transiting from trough Vt to crest Vc. In some
embodiment aspects, the unit of measurement of the brightness in
the brightness distribution is a grayscale level, and thus the unit
of measurement of the number of grayscale pixels of the tangent is:
grayscale level/number of pixels.
[0075] The processing unit 120 compares the number of grayscale
pixels of each tangent with a predetermined number of grayscale
pixels (step S47). If the number of grayscale pixels of each
tangent is less than the predetermined number of grayscale pixels,
it means: sharpness of the object image M1 is sufficient; and the
processing unit 120 does not adjust the gain of the image capturing
unit 110, the fill light intensity of the fill light unit 130, and
the shutter speed of the image capturing unit 110 (step S48). If
the number of grayscale pixels of any tangent is greater than the
predetermined number of grayscale pixels, it means: sharpness of
the object image M1 is insufficient; and the processing unit 120
enables the image capturing unit 110 to increase its shutter speed
(step S49), so as to increase the sharpness of the object image M1
in the driving image F1 captured after the fine-tuning step.
[0076] In some embodiment aspects, the predetermined number of
grayscale pixels falls within a specific numeric range, say, 0 to 2
(grayscale level/number of pixels), but the present disclosure is
not limited thereto.
[0077] In conclusion, in step S38 through step S40, the processing
unit 120 confirms the image quality of the driving images F1
according to a waveform of the brightness distribution of the
object image M1 in the driving images F1 to therefore enable quick
feedback and perform fine-tuning accordingly, so as to obtain the
driving images F1 with enhanced image quality quickly.
[0078] In some embodiments, in step S10 through step S33 of the
image capturing method, the processing unit 120 identifies a
currently appropriate shutter speed such that the driving image F1
captured by the image capturing unit 110 does not blur. Afterward,
in step S34 of the image capturing method, the processing unit 120
identifies a currently appropriate fill light intensity or gain
such that the driving image F1 captured by the image capturing unit
110 has appropriate brightness. Furthermore, given the appropriate
shutter speed and fill light intensity or gain, the processing unit
120 performs the fine-tuning operation of step S35 through step S37
or step S38 through step S40 of the image capturing method to
further augment the detailed performance of the driving images
F1.
[0079] Therefore, in some embodiment aspects, the product of the
shutter speed of the image capturing unit 110, the gain of the
image capturing unit 110, and the fill light intensity of the fill
light unit 130 before and after the fine-tuning operation of step
S37 (or step S40) remains the same. For instance, if the processing
unit 120 enables the shutter speed to reduce to a half thereof, the
processing unit 120 enables the gain or fill light intensity to
double; hence, the product of the shutter speed, gain and fill
light intensity is substantially the same before and after the
fine-tuning operation; in other words, the fine-tuning operation
brings no great change in the product of the shutter speed, gain
and fill light intensity.
[0080] In some embodiments, the vehicular image pickup device 100
is for use in a detection system of the police forces. For
instance, the vehicular image pickup device 100 is mounted on a
police car. The vehicular image pickup device 100 is electrically
connected to an internal system of the police car, and the internal
system sends the captured driving image F1 to a back-end system.
The back-end system performs post-processing and image recognition
on the driving image F1, and thus assists the police in quickly
recording and recognizing license plates and car models. The object
image M1 in the driving image F1 is an image of a license plate or
an image of the car body. The character images W1 are images of
numerals or characters.
[0081] In conclusion, a vehicular image pickup device and an image
capturing method in the embodiments of the present disclosure set a
shutter speed according to a variance of an object image in driving
images so as to obtain sharp driving images, fine-tune a fill light
intensity or gain according to a grayscale quantity distribution of
the driving images so as to obtain driving images with appropriate
brightness, and fine-tune the shutter speed, fill light intensity
or gain according to a frequency spectrum of the driving images or
a brightness distribution of an object image so as to augment the
detailed performance of the driving images. Furthermore, the
vehicular image pickup device and the image capturing method in the
embodiments of the present disclosure dispense with the need to
wait for feedback from a back-end system and thus are capable of
confirming the image quality of the driving images and performing
fine-tuning operation; hence, the driving images of enhanced image
quality can be quickly obtained.
[0082] Although the present disclosure is disclosed above by
preferred embodiments, the preferred embodiments are not
restrictive of the present disclosure. Changes and modifications
made by persons skilled in the art to the preferred embodiments
without departing from the spirit of the present disclosure must be
deemed falling within the scope of the present disclosure.
Accordingly, the legal protection for the present disclosure should
be defined by the appended claims.
* * * * *