U.S. patent application number 17/485264 was filed with the patent office on 2022-03-31 for method of detecting the cleanliness of a lens using differential flat field correction of pupil incidence.
The applicant listed for this patent is MLOptic Corp. Invention is credited to Jiang He, Weida Liu, Teresa Zhang, Wei Zhou.
Application Number | 20220099523 17/485264 |
Document ID | / |
Family ID | |
Filed Date | 2022-03-31 |
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United States Patent
Application |
20220099523 |
Kind Code |
A1 |
He; Jiang ; et al. |
March 31, 2022 |
METHOD OF DETECTING THE CLEANLINESS OF A LENS USING DIFFERENTIAL
FLAT FIELD CORRECTION OF PUPIL INCIDENCE
Abstract
A method for detecting lens cleanliness of a lens in a
flat-field optical path, the flat-field optical path includes a
light source, the lens, a camera, the light source is a narrow-band
multispectral uniform surface light source, the camera's
light-sensitive surface is disposed perpendicular to an optical
axis of the lens and in the light position of the lens and a pupil
interposed between the lens and the light source, the method
including collecting the bright-field image data and dark-field
image data for a plurality of pupil aperture sizes through the
lens; for each pixel, performing a pupil differential flat field
correction to yield a plurality of PiPj pupil differentials; and
displaying the pupil differentials in the form of a plurality of
images to show uniformity of each the image, wherein a non-uniform
area on each the image is determined to have been caused by an
impurity of the lens.
Inventors: |
He; Jiang; (Hangzhou City,
CN) ; Zhang; Teresa; (Albany, NY) ; Zhou;
Wei; (Sammamish, WA) ; Liu; Weida; (Nanjing
City, CN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
MLOptic Corp |
Redmond |
WA |
US |
|
|
Appl. No.: |
17/485264 |
Filed: |
September 24, 2021 |
International
Class: |
G01M 11/02 20060101
G01M011/02; H04N 5/225 20060101 H04N005/225; G06T 5/50 20060101
G06T005/50 |
Foreign Application Data
Date |
Code |
Application Number |
Sep 27, 2020 |
CN |
2020110299829 |
Claims
1. A method for detecting lens cleanliness of a lens in a
flat-field optical path, the flat-field optical path comprises a
light source, the lens, a camera, the light source is a narrow-band
multispectral uniform surface light source, the camera's
light-sensitive surface is disposed perpendicular to an optical
axis of the lens and in the light position of the lens and a pupil
interposed between the lens and the light source, said method
comprising: (a) collecting the bright-field image data and
dark-field image data for a plurality of pupil aperture sizes
through the lens; (b) for each pixel, performing a pupil
differential flat field correction to yield a plurality of PiPj
pupil differentials, wherein a PiPj pupil differential=(pupil Pi
bright-field image data-pupil Pi dark-field image data)/(pupil Pj
bright-field image data-pupil Pj dark-field image data) and Pi and
Pj are two different pupils, i is an index ranging from 1 to N, j
is an index ranging from 1 to N and N is the number of pupils; and
(c) displaying said pupil differentials in the form of a plurality
of images to show uniformity of each said image, wherein a
non-uniform area on each said image is determined to have been
caused by an impurity of the lens.
2. The method of claim 1, wherein: (a) said P is 3; (b) pupil P1
aperture size is 3 mm; (c) pupil P2 aperture size is 5 mm; (d)
pupil P3 aperture size is 6 mm; (e) P1P2 pupil
differential=(bright-field image data for pupil P1-dark-field image
data for pupil P1)/(bright-field image data for pupil P2-dark-field
image data for pupil P2); (f) P1P3 pupil differential=(bright-field
image data for pupil P1-dark-field image data for pupil
P1)/(bright-field image data for pupil P3-dark-field image data for
pupil P3); (g) P2P1 pupil differential=(bright-field image data for
pupil P2-dark-field image data for pupil P2)/(bright-field image
data for pupil P1-dark-field image data for pupil P1); (h) P2P3
pupil differential=(bright-field image data for pupil P2-dark-field
image data for pupil P2)/(bright-field image data for pupil
P3-dark-field image data for pupil P3); (i) P3P1 pupil
differential=(bright-field image data for pupil P3-dark-field image
data for pupil P3)/(bright-field image data for pupil P1-dark-field
image data for pupil P1); and (j) P3P2 pupil
differential=(bright-field image data for pupil P3-dark-field image
data for pupil P3)/(bright-field image data for pupil P2-dark-field
image data for pupil P2).
3. The method of claim 2, wherein said plurality of images comprise
six images comprising said P1P2 pupil differential, said P1P3 pupil
differential, said P2P1 pupil differential, said P2P3 pupil
differential, said P3P1 pupil differential and said P3P2 pupil
differential.
Description
PRIORITY CLAIM AND RELATED APPLICATIONS
[0001] This non-provisional application claims the benefit of
priority from Chinese Pat. App. No. 2020110299829 filed on Sep. 27,
2020. Said application is incorporated by reference in its
entirety.
BACKGROUND OF THE INVENTION
1. The Field of the Invention
[0002] The present invention relates to a lens inspection method.
More specifically, the present invention is directed to a method
for detecting lens cleanliness using differential flat field
correction of a pupil.
2. Background Art
[0003] Cleanliness is an important indicator of an imaging system
and cleanliness is directly related to stray light, ghosting,
uniformity and other key imaging factors. In a lens manufacturing
process, the generation of surface defects is often unavoidable. In
general, surface defects are local physical or chemical properties
of product surface uneven areas, such as inclusions, damage,
stains, etc., all having adverse impacts on the cleanliness of the
product. Therefore, a lens manufacturer attaches great importance
to lens cleanliness inspection, through timely discovery of surface
defects of the lens, effective control of product quality, further
analysis and solution of problems in the production process,
thereby eliminating or reducing the generation of defective
products.
[0004] Finished lens are predominantly visually inspected. Such
method of inspection yields a low sampling rate and accuracy, is
real-time poor, inefficient and labor-intensive. These shortcomings
are further exacerbated by inspectors' work experience and skills
while machine vision-based inspection methods can largely overcome
the shortcomings.
[0005] Machine vision can be utilized in non-contact and
non-destructive automatic inspections, therefore making it an
effective means to achieve equipment automation, intelligence and
precision control, with advantages in safety, reliability, wide
spectral response ranges, reduction of long working hours in harsh
environments and high productivity. Machine vision includes an
image analysis module, a data management module and a human-machine
interface module. An image acquisition module can include a
charge-coupled device (CCD) camera, an optical lens, a light source
and its clamping device, etc. Its function is to complete the
acquisition of images of a product surface. Under the illumination
of a light source, a surface of a product is imaged on the camera
sensor through an optical lens and the light signal obtained of the
surface of the product is converted into an electrical signal,
which is then converted into a digital signal that can be processed
by a computer. Currently, industrial cameras are mainly based on
CCD or complementary metal oxide semiconductor (CMOS) chip
technology. CCD is currently the most commonly used image sensor
for machine vision. A light source directly affects image quality
and its role is to overcome ambient light interference, to ensure
image stability and result in images with the highest possible
contrast. Currently used light sources are halogen lamps,
fluorescent lamps and light-emitting diode (LED). An LED light
source is beneficial as it comes in a small form factor, is low in
power consumption, is fast in response time, is a good
light-emitting monochrome, is highly reliable, is a uniform and
stable light, is easy to integrate and is applicable to a wide
range of applications.
[0006] Illumination systems composed of light sources can be
divided into bright-field and dark-field illumination, structured
light illumination and stroboscopic illumination according to their
illumination methods. Since the bright-field signal itself carries
information about the relative illuminance of the large-angle field
of view, it can have a non-negligible effect on imaging. However,
the manner in which the influence of a low relative illuminance of
a large-angle field of view is suppressed, the manner in which the
observable range of the impurity to be detected is amplified and
the manner in which the detection efficiency of impurity is
effectively improved, are the emphases of current researches in the
field of lens inspection.
SUMMARY OF THE INVENTION
[0007] In accordance with the present invention, there is provided
a method for detecting lens cleanliness of a lens in a flat-field
optical path, the flat-field optical path including a light source,
the lens, a camera, the light source is a narrow-band multispectral
uniform surface light source, the camera's light-sensitive surface
is disposed perpendicular to an optical axis of the lens and in the
light position of the lens and a pupil interposed between the lens
and the light source, the method including: [0008] (a) collecting
the bright-field image data and dark-field image data for a
plurality of pupil aperture sizes through the lens; [0009] (b) for
each pixel, performing a pupil differential flat field correction
to yield a plurality of PiPj pupil differentials, wherein a PiPj
pupil differential=(pupil Pi bright-field image data-pupil Pi
dark-field image data)/(pupil Pj bright-field image data-pupil Pj
dark-field image data) and Pi and Pj are two different pupils, i is
an index ranging from 1 to N, j is an index ranging from 1 to N and
N is the number of pupils; and [0010] (c) displaying the pupil
differentials in the form of a plurality of images to show
uniformity of each of the plurality of the images, wherein a
non-uniform area on each the image is determined to have been
caused by an impurity of the lens.
[0011] In one embodiment, the P is 3; pupil P1 aperture size is 3
mm; pupil P2 aperture size is 5 mm; pupil P3 aperture size is 6 mm;
P1P2 pupil differential=(bright-field image data for pupil
P1-dark-field image data for pupil P1)/(bright-field image data for
pupil P2-dark-field image data for pupil P2); P1P3 pupil
differential=(bright-field image data for pupil P1-dark-field image
data for pupil P1)/(bright-field image data for pupil P3-dark-field
image data for pupil P3); P2P1 pupil differential=(bright-field
image data for pupil P2-dark-field image data for pupil
P2)/(bright-field image data for pupil P1-dark-field image data for
pupil P1); P2P3 pupil differential=(bright-field image data for
pupil P2-dark-field image data for pupil P2)/(bright-field image
data for pupil P3-dark-field image data for pupil P3); P3P1 pupil
differential=(bright-field image data for pupil P3-dark-field image
data for pupil P3)/(bright-field image data for pupil P1-dark-field
image data for pupil P1); and P3P2 pupil differential=(bright-field
image data for pupil P3-dark-field image data for pupil
P3)/(bright-field image data for pupil P2-dark-field image data for
pupil P2).
[0012] In one embodiment, the plurality of images includes six
images including the P1P2 pupil differential, the P1P3 pupil
differential, the P2P1 pupil differential, the P2P3 pupil
differential, the P3P1 pupil differential and the P3P2 pupil
differential.
[0013] An object of the present invention is to provide a method
for detecting lens cleanliness using pupil differential flat field
correction in order to effectively improve the efficiency of
impurity detection.
[0014] Whereas there may be many embodiments of the present
invention, each embodiment may meet one or more of the foregoing
recited objects in any combination. It is not intended that each
embodiment will necessarily meet each objective. Thus, having
broadly outlined the more important features of the present
invention in order that the detailed description thereof may be
better understood, and that the present contribution to the art may
be better appreciated, there are, of course, additional features of
the present invention that will be described herein and will form a
part of the subject matter of this specification.
BRIEF DESCRIPTION OF THE DRAWINGS
[0015] In order that the manner in which the above-recited and
other advantages and objects of the invention are obtained, a more
particular description of the invention briefly described above
will be rendered by reference to specific embodiments thereof which
are illustrated in the appended drawings. Understanding that these
drawings depict only typical embodiments of the invention and are
not therefore to be considered to be limiting of its scope, the
invention will be described and explained with additional
specificity and detail through the use of the accompanying drawings
in which:
[0016] FIG. 1 depicts a test system for the differential flat-field
correction of an inferior pupil.
[0017] FIG. 2 depicts an image of the differential flat-field
correction results for three different pupils.
[0018] FIG. 3 depicts a combined arrangement of differential
flat-field correction of pupils.
PARTS LIST
[0019] 2--lens [0020] 4--camera [0021] 6--light source [0022]
8--pupil
DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT
[0023] There is provided a method for detecting lens cleanliness
using differential flat-field correction of an input pupil. The
method includes first building a flat-field test optical path. The
flat-field test optical path includes a light source, a lens to be
measured and a monochrome camera. The monochrome camera's
light-sensitive surface is placed perpendicular to the lens optical
axis of the lens under test and shifted to the light position of
the lens to be measured. The light source is a narrow-band uniform
surface light source; the bright-field image data is defined as the
data collected when the brightest value at the center of the field
of view is 80% to 90% of the saturation value, and the dark-field
image data is the data collected when there is no signal input; the
exposure time is fixed, and the brightness of the light source is
adjusted to acquire bright-field and dark-field image data. The
method further includes installing a pupil in front of the lens to
be measured and measuring the bright-field image data and
dark-field image data at different apertures of the pupil. For a
plurality of pupils, the dark-field image data at each pupil is
measured separately and the bright-field and dark-field image data
sets for each pixel at each pupil are obtained. The method further
includes performing the pupil-differential flat field correction
operation on each pixel where PiPj in pupil
differential=(bright-field image data for pupil Pi-dark-field image
data for pupil Pi)/(bright-field image data for pupil Pj-dark-field
image data for pupil Pj), Pi and Pj are two different kinds of
pupils, i is an index ranging from 1 to N, j is an index ranging
from 1 to N and N is the number of pupils. In the installing and
measuring step, the dark-field image data for different incident
pupils are acquired separately. The matrix of each pixel's pupil
differential is then displayed in the form of an image for the
determination of the lens cleanliness.
[0024] The performing step further includes performing the same
operation on each pixel, therefore traversing pupil P1, pupil P2,
pupil P3, . . . pupil PN-1, and pupil PN. For N pupils,
N.times.(N-1) combinations of pupil differentials are obtained.
Preferably, for P1, a small hole with an aperture diameter of 3 mm
is used. For P2, a small hole of 5 mm is used, and a small hole of
6 mm is used for P3. P=3 as there are three pupils of different
sizes. The aperture size should effectively take advantage of the
adjustment range of the light source of the test system. The
aperture size should not be too large and it should be evenly
distributed within the optional range. The following flat-field
correction operation is performed on the bright-field image data
and dark-field image data of each pixel for the plurality of pupils
and different aperture sizes.
P1P2 pupil differential=(bright-field image data for pupil
P1-dark-field image data for pupil P1)/(bright-field image data for
pupil P2-dark-field image data for pupil P2).
P1P3 inlet differential=(bright-field image data in P1-dark-field
image data in P1)/(bright-field image data in P3-dark-field image
data in P3).
P2P1 pupil differential=(bright-field image data for pupil
P2-dark-field image data for pupil P2)/(bright-field image data for
pupil P1-dark-field image data for pupil P1).
P2P3 pupil differential=(bright-field image data for pupil
P2-dark-field image data for pupil P2)/(bright-field image data for
pupil P3-dark-field image data for pupil P3).
P3P1 pupil differential=(bright-field image data for pupil
P3-dark-field image data for pupil P3)/(bright-field image data for
pupil P1-dark-field image data for pupil P1).
P3P2 pupil differential=(bright-field image data for pupil
P3-dark-field image data for pupil P3)/(bright-field image data for
pupil P2-dark-field image data for pupil P2).
[0025] The six pupil differentials are displayed in the form of six
images for the determination of lens cleanliness.
[0026] Compared to existing technology, the invention has the
following significant effects: As only the position of the sensor
surface of the camera is shifted during the measurement process,
the method is easy to be carried out. There are few pre-conditions
applicable to a limited number of test equipment. The influence of
low relative illumination of the large-angle field of view is
suppressed. The signal-to-noise ratio of the large field of view
range is improved. Edge enhancement of impurity imaging is
obtained. The imaging offset of different pupils in the CCD has a
definite pattern. After offsetting an impurity relative to the
optical center into symmetrical distributions with differential
impurity imaging, observable patterns of the impurity are then
unified.
[0027] The technical scheme of the invention is described in detail
below in connection with the drawings and specific embodiments.
There is provided a method for detecting lens cleanliness using
differential flat field correction of the pupil, the method
including:
(a) providing a flat-field test light path, the light path
including a narrow-band uniform surface light source, the lens to
be tested and a monochrome camera that meets the resolution
requirements. Camera resolution is the main factor that affects the
detection range. It is necessary to determine the monochrome camera
that meets the resolution requirement according to the detection
accuracy. In this example, the narrow-band uniform surface light
source uses an 8-inch monochromatic integrating sphere with a
center wavelength of 520 nm and a half-peak width of 20 nm. The
lens is mounted onto a V-block tool. The lens is disposed at a
large field of view, e.g., 120*120 degrees view angle. The camera
is disposed in a manner where the camera's light-sensitive surface
is perpendicular to the optical axis of the lens and the camera is
translated to a position to detect light through the lens. In this
example, the camera uses a pixel size of 5.5 um and a pixel count
of 8000*6000, placed at the rear focal plane of the lens; (b)
Placing the pupil in front of the lens to be measured and measuring
the bright-field and dark-field image data under the pupil. The
bright-field image data is the data obtained when the brightest
value at the center of the field of view is 80% to 90% of the
saturation value, and the dark-field image data is the data
collected when there is no signal input. The measuring step is
performed with the exposure time fixed, the brightness of the light
source adjusted so that the camera output falls within its range.
The image data can then be collected. Different pupil dark-field
image data is collected separately to improve data accuracy. In
this example, pupil A is a small hole with an aperture of 3 mm. The
design pupil position of the lens to be measured is located outside
the front face of the lens, and the lens barrel is designed with
mounting threads that allow the hole of pupil A to be mounted in
the design specified position.
[0028] In this example, the camera exposure time is fixed at 50 ms,
the integrating sphere is adjusted to output 520 nm monochromatic G
light, and the output is adjusted to 0 Nits, i.e., no light output,
and the camera acquires images as dark-field image data. When the
output is 50 Nits and the integrating sphere is configured to
output 520 nm G light, the G light is adjusted such that the camera
center Region of Interest (ROI) of 1000*1000 pixels is disposed at
an average value of 80% of the maximum range. The camera functions
in a 12-bit mode, i.e., the average gray value of about 3300, and
the image is collected as bright-field image data.
(c) changing the pupil of the optical system and repeating the
placing step to measure the bright-field and dark-field image data
under different pupils.
[0029] In general, dark-field image data for an optical system is
universal. In this scenario which involves switching of the pupil
of the optical system, the dark-field image data is measured
separately for each pupil switch in order to eliminate potential
negative effects. The measurement procedure is similar to that for
pupil A. The camera exposure time is fixed at 50 ms. Pupil A is
replaced with pupil B which has a hole diameter of 5 mm. The output
of the integrating sphere is adjusted and dark-field and
bright-field image data are collected. Pupil B is replaced with
pupil C which has a hole diameter of 6 mm. The output of the
integrating sphere is adjusted and dark-field and bright-field
image data are collected;
(d) For each pupil's bright-field image data and dark-field image
data, flat-field correction operations are performed.
[0030] Calculations for pupil differentials are carried out as
follows:
PiPj pupil differential=(bright-field image data for pupil
Pi-dark-field image data for pupil Pi)/(bright-field image data for
pupil Pj-dark-field image data for pupil Dj) where Pi and Pj are
two different kinds of pupils, i is an index ranging from 1 to N, j
is an index ranging from 1 to N and P is the number of pupils. For
pupil P1, pupil P2, pupil P3, . . . pupil PN-1, and pupil PN, there
are at most N*(N-1) combinations of different pupils as shown in
FIG. 3. The results obtained from different pupil combinations vary
depending on the physical properties of the impurities, including
but not limited to size, three-dimensional shape, transmittance,
refractive index, etc. Therefore, traversing various pupil
combinations enriches the detection information and improves the
judgment efficiency. In this example, six sets of data are obtained
for the bright-field and dark-field of each of the three types of
pupils in the camera, i.e., each pixel of the camera has six sets
of data independent of other pixels, and these data exist in the
form of a matrix. For each pixel, a flat-field correction is
performed, and the data processing for each pixel is independent of
the other pixels. The following six differential operations are
obtained:
AB pupil differential=(A pupil bright-field image data-dark-field
image data)/(B pupil bright-field image data-dark-field image
data).
AC pupil differential=(A pupil bright-field image data-dark-field
image data)/(C pupil bright-field image data-dark-field image
data).
BA pupil differential=(B pupil bright-field image data-dark-field
image data)/(A pupil bright-field image data-dark-field image
data).
BC pupil differential=(B pupil bright-field image data-dark-field
image data)/(C pupil bright-field image data-dark-field image
data).
CA pupil differential=(C pupil bright-field image data-dark-field
image data)/(A pupil bright-field image data-dark-field image
data).
CB pupil differential=(C pupil bright-field image data-dark-field
image data)/(B pupil bright-field image data-dark-field image
data).
[0031] The resulting matrix of pupil differentials is displayed
directly in the form of an image for the determination of lens
cleanliness. As can be seen from the differentials, the
differential flat field correction results are less affected by the
intensity distribution of the image itself, which can suppress the
effect of low relative illumination of the large-angle field of
view. At a first location, a first data point appears smaller than
the surrounding pixels and the image is presented as a dark spot.
At a second location, a second data point appears larger than the
surrounding pixels and the image is presented as a bright spot. The
impurity information is extracted and enlarged in the positive and
negative directions. The distribution of the two points of light
and dark is shown. There is a uniform pattern of distribution where
two positions of the same impurity overlap one another and the
edges of the overlap show a clear contrast with an edge-enhancing
effect. During the entire inspection, the optical system does not
move, only the pupil size changes. This method is applicable when
the pupil position is on the outside of the lens or when there is
an adjustable pupil inside the lens.
* * * * *