U.S. patent application number 12/674918 was filed with the patent office on 2011-09-01 for method and system for evaluating brightness values in sensor images of image-evaluating adaptive cruise control systems, especially with respect to day/night distinction.
This patent application is currently assigned to VALEO SCHALTER UND SENSOREN GMBH. Invention is credited to Cathy Boon, Andreas Kuehnle.
Application Number | 20110211071 12/674918 |
Document ID | / |
Family ID | 40429439 |
Filed Date | 2011-09-01 |
United States Patent
Application |
20110211071 |
Kind Code |
A1 |
Kuehnle; Andreas ; et
al. |
September 1, 2011 |
METHOD AND SYSTEM FOR EVALUATING BRIGHTNESS VALUES IN SENSOR IMAGES
OF IMAGE-EVALUATING ADAPTIVE CRUISE CONTROL SYSTEMS, ESPECIALLY
WITH RESPECT TO DAY/NIGHT DISTINCTION
Abstract
The invention proposes a method and an arrangement for
evaluating sensor images of an image-evaluating environment
recognition system on a carrier, in which, in order to distinguish
the light conditions in the area of the image-evaluating
environment recognition system with regard to day or night, at
least the gain and/or the exposure time of the at least one image
sensor detecting the environment is/are monitored, a profile of the
gain and/or the exposure time against time with relatively high
gain or relatively long exposure times characterizing night-time
light conditions, and a profile of the gain and/or the exposure
time with relatively low gain and/or relatively short exposure
times characterizing daytime light conditions. The environment
recognition system according to the invention can also be used to
search the detected environment for bright objects, the headlights
of another carrier being used as additional information, for
example.
Inventors: |
Kuehnle; Andreas; (Villa
Park, CA) ; Boon; Cathy; (Orange, CA) |
Assignee: |
VALEO SCHALTER UND SENSOREN
GMBH
Bietigheim-Bissingen
DE
|
Family ID: |
40429439 |
Appl. No.: |
12/674918 |
Filed: |
August 28, 2008 |
PCT Filed: |
August 28, 2008 |
PCT NO: |
PCT/EP08/07033 |
371 Date: |
February 24, 2010 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
60966719 |
Aug 28, 2007 |
|
|
|
Current U.S.
Class: |
348/149 ;
348/E7.085 |
Current CPC
Class: |
G06K 9/00798 20130101;
G06K 9/00791 20130101; G06K 9/00825 20130101; G06K 9/2027
20130101 |
Class at
Publication: |
348/149 ;
348/E07.085 |
International
Class: |
H04N 7/18 20060101
H04N007/18 |
Claims
1. A method for evaluating sensor images of an image-evaluating
environment recognition system on a carrier having a driver
assistance system, wherein the driver assistance system has a
lane-keeping assistance system, the method comprising: monitoring
at least one of a gain and an exposure time of the sensor images
detecting the environment to distinguish light conditions in an
area of the image-evaluating environment recognition system with
regard to day or night, wherein a state recognition profile of the
gain and/or the exposure time against time with relatively high
gain or relatively long exposure times characterizes night-time
light conditions, and the state recognition profile of the gain
and/or the exposure time with relatively low gain and/or relatively
short exposure times characterizes daytime light conditions.
2. The method according to claim 1, wherein the profile is
determined by carrying out an instantaneous daytime or night-time
recognition process in regular cycles using one of the
instantaneous gain and the instantaneous exposure time of the image
sensor, and wherein the method further comprises storing a number
of previous daytime or night-time recognition processes which
represent the profile in addition to the current daytime or
night-time recognition process, said number corresponding to a
predefined period of time.
3. The method according to claim 1, wherein, in the event of an
inconclusive assignment to a daytime or a night-time state, a third
setting is provided for the image sensor, wherein the third setting
does not contribute to a conclusive statement of the daytime or the
night-time state.
4. The method according to claim 3, an average value of the state
recognition profile is used to determine the third setting in order
to determine a state lying between a daytime state and a night-time
state, wherein the average value is formed proportional to the
state recognition profile or with the aid of a lookup table.
5. The method according to claim 1, wherein the environment
detected using the environment recognition system is searched for
bright objects which indicate switched-on headlights of another
carrier, wherein the occurrence of bright objects is then used as
additional information.
6. The method according to claim 5, wherein additional information
used for distinguishing the daytime or night-time state further
comprises indication objects which are recognized in a detected
environment, wherein indication objects appear different by day and
night.
7. The method according to claim 6, further comprising: determining
wherein a frequency with which the bright objects and indication
objects are found in the detected environment; and establishing a
connection between a night-time state and a predefined frequency of
the occurrence of the bright and indication objects in an
environment.
8. An arrangement for evaluating sensor images of an
image-evaluating environment recognition system on a carrier having
a driver assistance system, wherein the image-evaluating
environment recognition system comprises: an image sensor, an
electronic camera which is fitted to a vehicle, wherein the vehicle
is a carrier provided with a lane-keeping assistance system,
wherein the camera is configured to continuously record the front
area in a direction of travel of the vehicle on a roadway wherein
the camera and the image sensor capture a sensor image constructed
from pixels comprising brightness values and colour values an
evaluation unit configured to distinguish light conditions in an
area of the image-evaluating environment recognition system with
regard to day or night using a gain and/or an exposure time of the
camera which records the environment.
9. The arrangement according to claim 8, further comprising:
signaling the evaluation unit, based on the determination of a
daytime or a night-time state, to apply parameters and presettings
used to set a video-based or image-based driving assistance system
the daytime or night-time state.
10. The arrangement according to claim 9, wherein a speed of the
vehicle, is applied to the evaluation unit.
11. A computer program product stored on a computer-usable medium,
comprising computer-readable program instructions which, when the
computer program product is executed on a microprocessor with
associated storage means, cause said microprocessor or computer to
carry out a method according to claim 1.
Description
PRIOR ART
[0001] The invention relates to a method and an arrangement for
evaluating brightness values in sensor images of an
image-evaluating environment recognition system, in particular with
regard to distinguishing between day and night, such as is
preferably used in driving assistance systems in motor vehicles,
according to the precharacterizing clause of Method Claim 1 et seq.
and the arrangement according to Claim 8 et seq., as well as to a
computer program product according to Claim 11.
[0002] Such driving assistance systems are used to assist a driver
of a motor vehicle in carrying out particular operations in road
traffic and are already used for a wide variety of tasks. For
example, DE 10 2004 017 890 A1 discloses that a so-called LIDAR
radar sensor is used to detect a predefined area in the direction
of travel ahead of the vehicle in terms of particular objects, and
particular safety functions can be triggered in good time by means
of corresponding evaluation of the sensor signals. Examples of such
vision-based or image-based driving assistance systems which
attempt to understand or interpret a roadway situation or a scene
are sufficiently well-known lane-keeping assistants, lane departure
warning assistants, collision warning assistants or the like.
[0003] These systems which are known per se can be used, for
example, as part of adaptive cruise control and/or inter-vehicle
distance control of a vehicle, wherein such a control process can
then be carried out without intervention by the driver, a
previously set driving speed and/or a previously set distance from
a vehicle travelling ahead or from items and/or objects located in
the direction of travel. This is generally done by correspondingly
taking into account the environment of the vehicle and, if
appropriate, further parameters, for example the weather conditions
and visibility conditions. Such a control system is also often
referred to as an adaptive cruise control system (ACC system). The
ACC system must be flexible enough, in particular in respect of the
increasing traffic density of the present time, in order to react
suitably to all driving situations. This in turn requires a
corresponding object-detection sensor system in order to supply the
measurement data which are necessary for the control process in
each driving situation.
[0004] For this purpose, camera images, video images or sensor
images are also used in image-evaluating or else so-called
vision-based driving assistance systems for environment detection
and recognition, wherein, in the known systems, objects, obstacles,
boundaries of roadways and lanes and distances therefrom are
determined from the camera images. For the actual capturing of
images, image sensors which are referred to as imagers are used in
so-called vision-based environment detection systems, which image
sensors then supply a camera image (also referred to as a sensor
image) of the detected environment, the pixels or image areas of
which can be evaluated in terms of intensity, contrast, colour or
other parameters using corresponding data-processing means.
[0005] In this case, the sensor images of an identical scene or an
identical roadway situation may have a different appearance
depending on the external lighting. Environment recognition systems
in video-based driving assistance systems which attempt to
interpret the same scene or roadway situation with different
lighting may therefore have problems dealing with these different
conditions during evaluation. The different appearance on account
of changed lighting often requires readjustment or adjustment of
the control algorithms, parameters or presettings needed or used to
understand or interpret the scene or roadway situation.
[0006] A particularly frequent example of a scene which has a
different appearance depending on the lighting is a traffic
situation with vehicles which travel with the vehicle lighting
switched on at night and with the vehicle lighting switched off
during the day. Recognition of other vehicles by a vehicle with an
image-based driving assistance system may thus be made more
difficult or impaired depending on the light conditions.
Recognition of lane and/or roadway markings by an abovementioned
driving assistance system or by the environment recognition system
which interprets the scene or roadway situation may also be made
more difficult or impaired during a change from day to night.
DISCLOSURE OF THE INVENTION
[0007] The invention is based on a method for evaluating sensor
images of an image-evaluating environment recognition system on a
carrier, for example a vehicle in road traffic, possibly taking
into account the vehicle's own movement, in which, in order to
distinguish the light conditions in the area of the
image-evaluating environment recognition system with regard to day
or night, at least the gain and/or the exposure time of the at
least one image sensor detecting the environment is/are
advantageously monitored according to the invention. A profile of
the gain and/or the exposure time against time with relatively high
gain or relatively long exposure times will characterize night-time
light conditions, and a profile of the gain and/or the exposure
time with relatively low gain and/or relatively short exposure
times will characterize daytime light conditions. However, further
additional information may also be used in this case to make a
statement on a daytime or night-time state.
[0008] In order to determine a daytime or night-time state, it is
thus possible to evaluate at least the profile of the gain and/or
the exposure time of the image sensor in a predefined period of
time by determining, for example, whether a significant part or a
sufficiently large part of this profile corresponds to a daytime or
night-time state.
[0009] The inventive method for determining a daytime or night-time
state of a scene or roadway situation detected in a video-based or
image-based manner using at least one image sensor therefore uses a
different light intensity of the scene or roadway situation by day
or by night to the effect that a statement on a daytime or
night-time state can therefore be made in a simple manner.
[0010] The invention makes it possible to carry out an
instantaneous daytime or night-time recognition process in regular
cycles using the instantaneous gain and/or the instantaneous
exposure time of the image sensor, a number of previous stored
daytime or night-time recognition processes which may represent a
profile that can be evaluated also being able to be evaluated in
addition to the current or last daytime or night-time recognition
process, said number corresponding to a predefinable period of time
and the period of time on which the profile is based also being
able to be variable. In this case, a sufficient number of previous
daytime or night-time recognition processes which represent the
profile or the development of the situation should be present in
order to make a statement on a daytime or night-time state, which
number can be gathered from the profile.
[0011] If there is no difference from a previously or recently made
statement on a daytime or night-time state, for example because
there is not a sufficient number of daytime or night-time
recognition processes for a new decision, the previously or
recently made statement preferably remains unchanged.
[0012] The profile or the temporal development may be determined by
carrying out an instantaneous daytime or night-time recognition
process in regular cycles using the instantaneous gain and/or the
instantaneous exposure time of the image sensor, a number of
previous daytime or night-time recognition processes being stored
in addition to the current or last daytime or night-time
recognition process, said number corresponding to a predefinable
period of time.
[0013] If the period of time over which the profile is tracked or
the number of stored previous daytime or night-time recognition
processes is variable, for example in order to avoid having to
imperatively resort to a long chain of previous night-time
recognition processes after turning off a vehicle at night and when
reusing the vehicle the next morning, an even better statement on a
daytime or night-time state can be made.
[0014] The method according to the invention can also be extended
by the fact that, in the event of an inconclusive assignment to a
daytime or night-time state, a third setting which does not
contribute to a conclusive statement on a daytime or night-time
state is provided for the image sensor in the environment
recognition system. An average value of the state recognition
profile can be used to determine the third setting in order to
determine a state lying between a daytime state and a night-time
state, the average value being formed, in particular, in a fashion
proportional to the profile or with the aid of a lookup table. The
average value is preferably formed in a fashion proportional to the
profile, for example proportional to the profile of the daytime or
night-time recognition processes carried out.
[0015] This particularly advantageous refinement of the invention
thus provides for an intermediate zone to correspond to a "neither
daytime nor night-time state" of the image sensor. Currently, such
a "neither daytime nor night-time state" initially results neither
in a daytime recognition process nor in a night-time recognition
process, that is to say the image sensor has in this case a gain
and/or an exposure time which, if permanently maintained, would not
result in any conclusive statement on a daytime or night-time
state. As a result of the fact that a "neither daytime nor
night-time state" is thus provided as a third setting, it is
possible to avoid frequently changing over between determination of
a daytime state and determination of a night-time state.
[0016] For example, for a profile with 40% daytime recognition, 50%
night-time recognition and 10% "neither daytime nor night-time
states", the parameters or presettings may be set or readjusted
with a 50/90 share of the setting range between day and night. A
proportionality which is not necessarily linear in this case may
thus be formed between the brightness state of the environment and
the parameter settings.
[0017] It is particularly advantageous if the environment detected
using the environment recognition system according to the invention
is searched for bright objects which indicate the headlights of
another carrier and whose occurrence is then used as additional
information. Additional environment-specific information may also
be used to distinguish the daytime or night-time state, which
environment-specific information includes, in particular, further
indication objects which are recognized in a detected environment
and whose different appearance by day or night is known. For
example, reflectors fitted to the surface of the roadway shine
brightly at night as a result of their highly reflective
properties; they are almost invisible or dark during the day.
[0018] For this purpose, bright objects in the form of headlights,
in particular on the front of a vehicle, may be determined in
particular, the occurrence of which is then used as additional
information. Such objects have, for example, a generally round or
elliptical shape and occur in pairs. They are thus generally easy
to identify during image evaluation.
[0019] In this case, it is likewise advantageous if the frequency
with which the bright objects and/or further environment-specific
information are/is found in the detected environment is determined,
a connection being established between a night-time state and a
predefined frequency of the occurrence of such objects in an
environment. One example is vehicle lights which are seen more and
more often at night, with the result that the quotient of the
number of lights found and the number of vehicles found
increases.
[0020] The area-specific knowledge thus preferably also includes
particular indication objects which can be identified in an
environment, for example objects which are used to delimit roadways
and lanes and the appearance of which is known, or other patterns
in the form of roadway or lane markings in the detected situations.
These also differ by day and by night, for example some appear to
be larger by night than by day.
[0021] The frequency of occurrence may in turn be included as
additional information in a statement or decision on a daytime or
night-time state. For example, a connection may be established
between an increasing frequency of the occurrence or observation of
indication objects with a known appearance at night in a scene or
situation and a decision or statement tending towards a night-time
state.
[0022] In the case of an advantageous arrangement for carrying out
the method described above, the image-evaluating environment
recognition system includes, as image sensor, an electronic camera
which is fitted to a vehicle as a carrier and continuously records
the front area (in the direction of travel) of the vehicle on a
roadway in such a way that a sensor image constructed from pixels
whose brightness values and, if appropriate, colour values image
the environment is respectively present. There is also an
evaluation unit which can be used to distinguish the light
conditions in the area of the image-evaluating environment
recognition system with regard to day or night on the basis of the
gain and/or the exposure time of the at least one camera which
records the environment.
[0023] In the case of such an arrangement, a signal from the
determination of the daytime or night-time state, that is to say in
particular parameters or presettings which can be used to set a
video-based or image-based driving assistance system with regard to
the daytime or night-time state, can then be applied to the
evaluation unit in a simple manner. In this case, it is
conceivable, for example, to set the parameters or presettings on a
sliding scale in such a manner that the best performance of an
environment recognition system which recognizes a situation in the
environment is achieved in conjunction with a video-based or
image-based driving assistance system.
[0024] In summary, the invention thus provides a method which makes
it possible to classify a lighting situation as a daytime or
night-time situation. This classification thus makes it possible to
recognize a roadway situation without errors independently of the
lighting state thereof.
[0025] The invention also proposes a computer program product
which, stored on a computer-usable medium, comprises
computer-readable program means which, in the event of the computer
program product being executed on a microprocessor with associated
storage means or on a computer, cause said microprocessor or
computer to carry out the method according to the invention or to
operate the arrangement.
BRIEF DESCRIPTION OF THE DRAWING
[0026] One exemplary embodiment of the invention is illustrated in
the figures of the drawing and is explained below. In the
drawing:
[0027] FIG. 1 shows a diagrammatic illustration of a vehicle having
a camera as part of an environment recognition system for
evaluating daytime and night-time states, additionally also using
the headlights of another vehicle, and
[0028] FIG. 2 shows a flowchart of the method features according to
the invention in an evaluation unit of the environment recognition
system.
DESCRIPTION OF THE EXEMPLARY EMBODIMENT
[0029] FIG. 1 diagrammatically reveals a situation of a vehicle 1
as a carrier of an environment recognition system which can move in
this case on a roadway 2 in the direction of an arrow 3. The
environment recognition system of the vehicle 1 has, as an image
sensor, a camera 4, in particular a digital video camera, which
records an area between dashed lines 5 and 6.
[0030] The roadway 2 is separated by a marking 7, and another
vehicle 8 which is fitted with front headlights 9 approaches on the
other side of the roadway. At an input 11, the digital data of the
pixel-comprising sensor image from the camera 4 and additionally,
for example at an input 12, also the current speed data of the
vehicle 1 are evaluated in an evaluation device 10.
[0031] In order to distinguish the light conditions in the area of
the image-evaluating environment recognition system on the vehicle
1 with regard to day or night, the gain and/or the exposure time of
the camera 4 is/are monitored in the evaluation device 10 according
to FIG. 1. In this case, a profile of the gain and/or the exposure
time against time with relatively high gain or relatively long
exposure times characterizes the night-time light conditions and a
profile of the gain and/or the exposure time with relatively low
gain and/or relatively short exposure times characterizes the
daytime light conditions.
[0032] In this case, however, it is also possible to use further
additional information to make a statement on a daytime or
night-time state. The environment recorded with the camera 4 is
searched for bright objects, the headlights 9 of the other vehicle
8 being used as additional information in the exemplary embodiment
shown here. Furthermore, it is also possible to use additional
environment-specific information (not explained in any more detail
here) to distinguish the daytime or night-time state, which
environment-specific information includes, in particular, further
indication objects which are recognized in a detected environment
and whose different appearance by day or night is known.
[0033] In order to detect a different light intensity which allows
a conclusion to be drawn on a daytime or night-time state, it is
generally possible to proceed using the flowchart according to FIG.
2, essentially the following method steps which are then explained
in detail using the flowchart according to FIG. 2 being carried out
in the evaluation unit 10 in this case: [0034] At least the gain
and/or the exposure time of the camera 4 is/are monitored. [0035] A
profile or a development with consistently high gain or
consistently long exposure times is used as an indication that it
is currently night-time. [0036] A profile or a development with
consistently low gain or consistently short exposure times is used
as an indication that it is currently daytime. [0037] The profile
or the development of the gain and/or the exposure times of the
image sensor or similar settings is/are preferably evaluated and it
is determined whether a significant part or a sufficiently large
part of this profile or this development corresponds to a daytime
or night-time state. [0038] A profile or a development of the
daytime and night-time decisions can subsequently then be stored,
which profile or development can then be used to make a subsequent
statement on a daytime or night-time state. [0039] The profile
(which can also be referred to as the history) or the temporal
development can be determined, for example, by carrying out an
instantaneous daytime or night-time recognition process in regular
cycles using the instantaneous gain and/or the instantaneous
exposure time of the image sensor. A number of previous daytime or
night-time recognition processes which represent the profile or the
development of the daytime or night-time recognition processes can
be stored in addition to the current or last daytime or night-time
recognition process, said number corresponding to a predefinable
period of time. [0040] The period of time may be variable, for
example in order to avoid having to imperatively resort to a long
chain of previous night-time recognition processes after turning
off a vehicle at night and when reusing the vehicle the next
morning, in order to make a statement on a daytime or night-time
state. [0041] In order to avoid frequently changing over between
determination of a daytime state and determination of a night-time
state, provision is preferably made of a "neither daytime nor
night-time state" which corresponds to an intermediate zone and
preferably provides neither daytime settings nor night-time
settings for the image sensor. Currently, such a state initially
results neither in a daytime recognition process nor in a
night-time recognition process, that is to say the image sensor has
a state, that is to say a gain and/or an exposure time, which
state, if permanently maintained, would not result in any
conclusive statement on a daytime or night-time state. [0042] This
"neither daytime nor night-time" state preferably also does not
contribute to a conclusive statement on a daytime or night-time
state. [0043] A sufficient number, which can be gathered from the
profile or the development for example, or a sufficient proportion,
which corresponds to a percentage for example, of previous daytime
or night-time recognition processes is preferably needed to make a
statement on a daytime or night-time state. [0044] If there is no
difference from a previously or recently made statement on a
daytime or night-time state, for example because there is not a
sufficient number of daytime or night-time recognition processes
for a new decision, the previous state is preferably retained or
the previously or recently made statement preferably remains
unchanged. [0045] According to the invention, additional
information may be used to make a statement or decision on a
daytime or night-time state. For example, it is conceivable to
search detected situations or scenes for bright objects in the form
of headlights, as illustrated in FIG. 1. Objects in the form of
headlights on the front of another vehicle 8 have, for example, a
generally round or elliptical shape and occur in pairs and at
approximately the same image height. [0046] The frequency with
which such objects are found in the detected situations or scenes
which are searched can also be monitored. A connection is
preferably established between an increasing frequency of the
occurrence or observation of such objects in a scene or a situation
and a decision or statement tending towards a night-time state.
[0047] Area-specific knowledge relating to how a scene or a
situation has a different appearance by day and by night can also
be used to make a statement or decision on a daytime or night-time
state. [0048] An example of such area-specific knowledge is the
fact that particular objects, for example reflectors which are
used, for example, to delimit roadways and lanes, appear larger by
night than by day. [0049] In this case, the frequency with which
objects having such properties or such an appearance occur, for
example, in a pattern in the form of roadway or lane markings can
then be monitored. In this case too, a connection is preferably
established between an increasing frequency of the occurrence or
determination of such objects in a scene or in a situation and a
decision or statement tending towards a night-time state. [0050]
The decision itself or the statement made need not necessarily be
binary, that is to say does not necessarily need to have only two
states, for example it is day or it is night. For example, an
average value of the daytime or night-time recognition processes
can be used, for example in a proportional manner, to set or
readjust the rules or presettings of a video-based or image-based
driving assistance system, which understands or interprets a
situation or a scene, or the image recognition system thereof. For
example, for a profile with 40% daytime recognition, 50% night-time
recognition and 10% "neither daytime nor night-time states", the
rules or presettings may be set or readjusted with a 50/90 share of
the setting range between day and night. [0051] Such setting or
readjustment can also be carried out in a non-linear manner, for
example with the aid of a lookup table.
[0052] A flowchart of the method according to the invention is now
explained by way of example using FIG. 2.
[0053] The method starts in a first method step 21. A daytime state
is set as the starting or initial value in a second method step 22.
A so-called frame is recorded in a third method step 23, which
frame contains at least the instantaneous gain and the
instantaneous exposure time of at least the camera 4 according to
FIG. 1, which records an environment as a roadway situation or
scene, at least at the time at which the environment is detected in
a video-based or image-based manner.
[0054] The gain and the exposure time of the at least one camera 4
are read from the frame in a fourth method step 24. In a fifth
method step 25 (inserted under A after the method step 24), an
enquiry may take place in order to determine whether a sufficiently
fast movement has taken place since the last frame was recorded,
for example in order to determine whether a sufficient distance on
the roadway 2 has been travelled since then. If this is the case,
the method proceeds with a sixth method step 26. If this is not the
case, a new frame is recorded again in the third method step 23.
However, the method according to the invention does not necessarily
presuppose any movement of the carrier and thus of the camera 4;
however, the vehicle's own movement is taken into account in the
exemplary embodiment described here.
[0055] The sixth method step 26 clarifies whether the instantaneous
exposure time and instantaneous gain stored in the recorded frame
correspond to an instantaneous daytime state or a night-time state
or a "neither daytime nor night-time state". The result is an
instantaneous daytime or night-time recognition process or an
instantaneous "neither daytime nor night-time state".
[0056] In a seventh method step 27, the knowledge obtained in the
sixth method step 26 is added to a profile. In an eighth method
step 28, an enquiry takes place in order to determine whether the
profile has a sufficient length. If this is the case, the method
continues with a ninth method step 29. If this is not the case, the
method continues with the third method step 23.
[0057] In the ninth method step 29, an enquiry takes place in order
to determine whether items of knowledge added to the profile in a
sufficient number are night-time decisions. If this is the case,
the method continues with a tenth method step 30. If this is not
the case, the method continues with an eleventh method step 31.
[0058] In the tenth method step 30, the statement that a night-time
state prevails is made. In the eleventh method step 31, an enquiry
takes place in order to determine whether items of knowledge added
to the profile in a sufficient number are daytime decisions. If
this is the case, the method continues with a twelfth method step
32. If this is not the case, the method preferably continues with
the third method step 23. In the twelfth method step 32, the
statement that a daytime state prevails is made.
[0059] In a thirteenth method step 33 which follows the tenth and
twelfth method steps 30, 32, the profile is erased and the method
continues in the third method step 23 again.
[0060] It is important to emphasize that it is not the aim or
objective of the invention to control lighting. Rather, the aim of
the invention is to describe or classify a lighting situation of an
environment, a scene or a roadway situation by monitoring the
camera and incident or process statistics. A result obtained
thereby in the form of the statement made is preferably used to set
the rules, parameters or presettings of a video-based or
image-based driving assistance system, which understands or
interprets the environment, or the environment recognition system
thereof, for example on a sliding scale, in such a manner that the
best performance is achieved.
[0061] The invention is industrially applicable, in particular, in
the field of the production and operation of video-based or
image-based driving assistance systems or video-based or
image-based video systems which can be used in road traffic. In
this case, it is particularly advantageous and also provided for
the driver assistance system to have a lane-keeping assistance
system.
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