BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention generally relates to security systems, specifically
to security systems which employ video equipment for motion detection. Disclosed
is a system which reduces the number of false alarms generated by video motion
detector systems in response to video image changes which are not related to motion.
2. Discussion of the Related Art
Video systems are well known in the field of security systems. In
a typical security system, one or more video cameras are placed so as to provide
a field of view of the area under surveillance. These video cameras convert a visual
image into an electronic form suitable for transmission. A control station, either
co-located within the surveillance area or remote from the area, receives the signals
from these cameras and displays the video image at a console, for security assessment
and recording. Typically, a person monitors the images from the cameras on a video
screen and initiates security measures if the received image indicates unauthorized
activities. Often the monitoring person (hereinafter the monitor) is responsible
for monitoring the images from multiple cameras simultaneously, and means are provided
to assist in this process.
Automated motion detection systems are employed to alert the monitor
of the presence of activity within the view of a camera, as typified in U.S. patent
4,458,266. These motion detection systems operate by detecting changes in the sequential
electronic images of the same scene. A change in the scene implies the entry or
exit of an item from that scene. When a change is detected, an alarm is sent to
the monitor for a security assessment. The monitor will view the sequence of images
which caused the alarm, as well as other images, from this camera or others, to
determine whether the alarm requires the initiation of security measures such as
notifying the police or activating a warning signal. These motion detection systems
can be co-located with the camera, or remote from the camera. They are often co-located
with the camera and operate so as to transmit the images to the control station
only in the event of an alarm, thereby saving communications bandwidth and costs.
Environmental changes will cause the video image to change; for example,
in an outside environment, the video image at sunset will be different from the
video image at noon. Because motion detectors operate by comparing video images
for changes, and environmental changes create such changes, means must be provided
to avoid the generation of an alarm signal in response to environmental changes.
Conventionally, noting that most environmental changes are slowly changing phenomenon,
motion detection systems avoid the generation of alarms in response to environmental
changes by comparing images which occur relatively closely spaced in time. That
is, for example, instead of comparing the image at noon with an image at sunrise,
the image at noon is compared to the image at a fraction of a second before noon.
A person or object entering the scene will introduce a noticeable change between
images of a fraction of a second difference in time, but the change of environment
in that same fraction of time will be insufficient to trigger an alarm. In the
conventional system, the compared image is continually updated, to maintain the
fraction of time difference between images. That is, following the aforementioned
comparison between the noon image and the noon-minus-a-fraction image, the noon-plus-a-fraction
image is compared to the noon image, and so on.
This sequential compare and update process results in motion detection
systems which are sensitive to relatively rapid changes to the scene, and are insensitive
to relatively slow changes to the scene, as desired. Because they are sensitive
to rapid changes in scenes, conventional motion detectors are sensitive to rapid
environmental changes as well. A lightning bolt at night will cause a significant
change to sequential video images, and will cause the motion detector associated
with these images to generate an alarm, obviating their effectiveness during a
lightning storm. The headlights of a car, illuminating the area within a camera's
field of view, will also trigger erroneous alarms, which often limits the choice
of placement or field of view of a security camera.
Security systems often also include a means for masking a portion
of the image area from motion detection. Such systems allow movement within the
masked areas, and sound an alarm for movement in other areas, both areas within
the field of view of the camera. An interior scene may, for example, comprise a
walkway adjacent to a secure area. Even though movement in the walkway can be masked
to prevent alarms being generated in response to such movement, the turning on
or turning off of the lighting for the walkway will cause the secure area image
to change, resulting in a false alarm.
SUMMARY OF THE INVENTION
Essentially, the invention describes a motion detector system which
is insensitive to environmental changes, including both rapidly and slowly changing
scenes. This invention, in its preferred embodiment, minimizes the likelihood of
false alarms while also minimizing the likelihood of bypassing a true alarm.
This invention is premised on the observation that environmental changes,
as discussed above, produce changes to the entire scene, whereas movement within
a scene is localized to a sub-area within the scene. In accordance with this invention,
changes in the video images are assessed for a global scene change, affecting a
large area of the scene. By assessing the images for changes affecting the entire
scene, environmental changes can be distinguished from motion induced changes.
Changes affecting the entire scene can be inhibited from generating alarms, thereby
reducing false alarms.
In a further embodiment, the local changes are compared to the global
scene change to determine if the local change is consistent with the global change.
Local changes which are inconsistent with the global change are subsequently assessed
for motion detection. In this way, motion induced local changes may trigger an
alarm, even though a global change may have occurred, contemporaneous with the
local motion. This feature limits the use, on the part of an intruder, of a diversionary
environmental change to mask the intruder's entry to a secured area.
These and other features of the invention will be readily apparent
to one versed in the art, in light of the drawings and detailed description following.
BRIEF DESCRIPTION OF THE DRAWINGS
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS OF THE INVENTION
- FIG. 1 shows a video security system with motion detection.
- FIG. 2 shows a flowchart for motion detection with global change insensitivity,
in accordance with this invention.
- FIG. 3 shows frames corresponding to random, intruder induced, and global changes,
in accordance with this invention.
- FIG. 4 shows a flowchart for computing a motion detection threshold.
Figure 1 shows a video security system with a motion detector, as
known in the current art. Video images 101 are produced by the camera 110. These
images are representative of the camera's field of view 112. The field of view
is established by the camera's location, orientation, and lens configuration. In
figure 1a, the video images 101 are simultaneously sent to the monitor station
120 and the motion detector 130. The motion detector 130 compares a frame of the
current image 136 to a frame of the prior image 137, under the control of a controller
139. The compare block 138 asserts an alert signal 131 whenever the current image
136 differs substantially from the prior image 137. The difference between the
images may be measured by the number of picture elements (pixels) having a different
value, for example. If the number of differing pixels exceeds a threshold value,
an alert is transmitted to the monitor station. The use of a threshold allows the
motion detector to be insensitive to small changes, such as caused when small animals
traverse the camera's field of view. After comparison, via the controller 139,
the current image 136 becomes the prior image 137, in preparation for receipt of
the next frame of video image 101. The motion detector 130 may contain an optional
mask feature, to block portions of the scene from motion detection. This blocking
out, or masking, is performed by the mask block 135. The mask identifies areas
of the image which should not be used by the compare block 138 in its determination
of whether an alert signal 131 should be asserted. The mask is applied to block
138 so that the differences between those pixel of the current image 136 and the
prior image 137, which correspond to the areas of the mask 135, are not used for
asserting the alert signal 131. Note that, in a typical system, the monitor station
receives the full, unmasked image, showing all motion, but the monitor is not alerted
to motion except in the unmasked areas.
Figure 1b shows a security system with a remote monitor station. Images
101 and alerts 131 are communicated to the monitor 120 via the transmitter 140
and receiver 150. Optionally, the transmitter 140 may be designed to only transmit
video images 101 upon command from the monitor, or upon an asserted alert signal
from the motion detector 131. Typically, the transmitter may contain one or more
video image buffers. Upon the detection of motion, as signalled by the alert signal
131, the transmitter will transmit the current video image, as well as prior and
subsequent images, to aid the monitor in an assessment of the security situation.
The motion detector 130 operates by comparing one image with another.
Rather than comparing the images on a pixel by pixel basis, groups of pixels within
an image are typically characterized by a single parameter, and this parameter
is compared, image to image. In this disclosure, the term frame is used to describe
this representation of the image, and within each frame are subelements referred
to as MCUs. An MCU refers to a grouping of pixels having a comparable parameter.
For example, an MCU may be defined as an 8 by 8 contiguous group of pixels, and
the parameter of this MCU may be the average luminosity of these 8 by 8 pixels.
A 320 by 240 pixel image would thus form a frame which is partitioned into a 40
by 30 matrix of 8 by 8 pixel MCUs, and the frame is stored as a 40 by 30 array
of the average pixel value within each MCU. If the average value of an individual
MCU changes substantially, from one image to the next, it can be assumed that something
has entered or exited the scene. The size of the MCU can be as small as a single
pixel; a larger size will result in the faster processing of sequential images,
but with an accompanying loss of resolution.
Also typical of common motion detection systems, a parameter is provided
to specify the minimum size of an object which will trigger an alarm. This parameter
may be specified as a minimum number of MCUs, or a particular arrangement of MCUs.
For example, one may specify that motion must be detected in at least five MCUs
before an alarm is triggered, or, in at least a two MCU by three MCU area. In this
manner, small animals, for example, will not trigger alarms, even though the specific
MCUs within which their image appear will show a difference from one frame to the
next. The minimum sized area required to trigger an alarm is termed herein as the
Figure 2 shows a flowchart for a Motion Detection System in accordance
with this invention. At block 200, the video image is processed to form a frame
which is stored as an MCU array. As mentioned above, the MCU array contains parameters
which characterize the image to the degree necessary for subsequent processing.
Each MCU could correspond to a single pixel, and the frame could contain the entire
video image, to whatever detail the camera 110 provides. To optimize processing,
however, the frame is typically an abstraction of the image which contains sufficient
detail to enable a comparison of one image to another, by comparing the parameters
contained in one frame to another. In the preferred embodiment, an MCU represents
an 8 by 8 grouping of pixels, and these 8 by 8 pixels are characterized by the
average value of their luminance; other characteristics of the pixels, such as
their composite colour, could also be utilized, in addition to, or in lieu of, the
luminance parameter. The MCU array is first assessed for a minimum light intensity,
at 210. This assessment is performed as a self test of the system, and may include
a test for a maximum intensity, minimum contrast, etc. This assessment also provides
for an alert to a potential purposeful obscuration of the camera, as well. If insufficient
light is detected, the error is reported 214 and no further processing is performed
on this image.
If sufficient light is detected, an initialization test is performed
at 220. If this is the first frame, a comparison cannot be performed, and the system
proceeds directly to update the reference MCU array at 270. The reference MCU array
is the MCU array to which subsequent MCU arrays are compared. In a typical embodiment,
this array is merely a copy of the current MCU; however, it may be advantageous
that the reference array is a composite of multiple prior images. For example,
in the preferred embodiment, the reference MCU is a recursive weighted average
of all prior images. This averaged MCU is found to be effective for suppressing
rapid image changes as might be caused by rustling leaves and such, while allowing
for gradual luminance changes as might be caused by sunrise, sunset, and so forth.
The reference MCU is assessed at 280 to compute parameters which will
be used for the comparison of subsequent frames. For example, in the preferred
embodiment, the variance or deviation in value among the MCU elements is indicative
of the contrast contained in the image. This contrast can be utilized to set a
minimum threshold for subsequent MCU comparisons. That is, in the subsequent MCU
comparisons, only those changes which exceed this threshold will be flagged as
noteworthy changes. The automatic adjustment of this threshold in proportion to
the contrast provides for consistent motion detection performance, even under significantly
different viewing conditions. If the image, for example, is produced on a bright
sunny day, one would expect a significant amount of contrast in the image, and,
correspondingly, significant changes in luminosity as the image changes, due either
to the random motion of items within the scene, or due to an intruder. To minimize
false alarms caused by random motions, the threshold value is set to be larger
than the changes in luminosity expected to be caused by these random motions. Thus,
the threshold should be high when the image contains a high degree of contrast.
When the same scene is viewed on a cloudy day, the contrast will be lower, as will
be the changes in luminosity as the image changes. The threshold value should be
adjusted downward for a less contrasted image to approximately maintain the same
degree of insensitivity to random motion while still maintaining the same degree
of sensitivity to the entry of an intruder. By setting the threshold in dependence
upon the contrast, the system provides for an automatic adjustment, thereby automatically
maintaining this consistency. Having created the reference image, and having set
the threshold level for subsequent comparisons, the process returns at 290, awaiting
the next image to arrive at 200.
Upon receipt of a subsequent image, the image is processed to produce
a new MCU array at 200, and checked for minimum light intensity at 210, as discussed
above. If it is not a first frame, it is compared to the aforementioned reference
MCU array to produce a Difference Array at 230. In the preferred embodiment, this
is an element by element subtraction of each corresponding MCU within the current
MCU and the reference MCU. The magnitude of the difference of each corresponding
MCU is stored in the Difference Array.
If an individual MCU's difference factor exceeds a detection threshold
value, as determined in 240, a Difference Flag is set, corresponding to this MCU,
in a Difference Flag Map at 250. The Difference Flag Map will contain, for example,
a one for each current MCU which differs from the reference MCU by the detection
threshold amount, and a zero otherwise. An intruder would create a cluster of ones
in this map at the location of the intrusion. The map is assessed at 260 to determine
if any clusters exist which exceed the aforementioned target size. If one or more
of such clusters exist, an alarm is sounded at 265. In either event, the reference
array is updated 270 and assessed 280 and the process returns to await the next
The updating of the reference array may be made to be dependent upon
whether an alarm was sounded. It may be preferable, for example, to not update
the reference, pre-alarm, image until some action is taken in response to the sounded
alarm. Similarly, other processing may be effected upon the sounding of the alarm,
and this process may be bypassed for subsequent frames, to allow such processes
to proceed uninterrupted.
The operation of this flowchart is detailed in figure 3. Figure 3A
represents a scene subject to random changes in luminosity; figure 3B represents
a scene upon the entry of an intruder; figure 3C represents a scene upon the occurrence
of a global change. In each of these figures, the Reference frame 310 is the same.
The Reference frame 310, the Subsequent frame 320A, 320B, 320C, and the Difference
frame 330A, 330B, 330C each comprises twenty MCUs 315, arranged in a five by four
matrix. Conceptually, these frames are arranged to represent a partitioning of
a scene as might correspond to camera 110's field of view 112. For example, if
the numbers shown within each MCU represent luminosity, the Reference frame 310
shows higher values in the upper region of the matrix, corresponding to the sky,
or ceiling lights, while the lower regions have lesser values, corresponding to
the ground, or flooring. Consistent with this invention, the structure and correspondence
of the frame representation may take on alternative forms, for example, for more
In figure 3B, the Subsequent frame 320A has entries which are representative
of random changes from the Reference frame. MCU 321 shows a value of 21, whereas
the corresponding MCU 311 in the Reference frame shows a value of 25. The magnitude
of the difference between MCU 321 and MCU 311 is shown as the value 4 in the corresponding
Difference frame MCU 331. Similarly, the values of MCU 332 and 333 correspond to
the magnitude of the differences between MCUs 322 and 312, and MCUs 323 and 313,
Assuming a threshold value of ten, a Difference Flags map, as would
be computed by block 250 in figure 2, is shown at 350A. The MCUs within the Difference
frame 330A whose values are at least ten have a corresponding 1 in the Difference
Flags map 350A. Difference Flags entry 353 has a value of 1, corresponding to the
Difference MCU 333 value of eleven, while the Difference Flags entries corresponding
to MCUs 331 and 332, with values 4 and 3 respectively, each have a value of 0 at
351 and 352. Although two of the entries in the Difference Flags map 350A contain
a 1, if the target size parameter of block 260 in figure 2 is, for example, two
contiguous MCUs, the alarm would not be sounded at 265.
Figure 3B corresponds to the entry of an intruder in the area corresponding
to the MCUs indicated at 341. The Difference MCUs at 342 show a large difference
between the MCUs at 341 and the MCUs at 340. Correspondingly, the Difference Flags
map shows a cluster of ones at 343. If this cluster exceeds the target size parameter,
for example two contiguous MCUs, the alarm will be sounded at 265.
As noted above with reference to figure 2, the Difference Array is
assessed at 240 and 250 to identify difference clusters. It is in this assessment
that global changes may be distinguished. A global change can be expected to introduce
changes to a majority of MCUs. Thus, if the Difference Array contains many changes,
rather than a few localized changes, it may be inferred that a global change has
occurred, rather than an intrusion. Any number of algorithms may be utilized to
assess whether the changes are widespread or localized. For example, a count of
the number of elements in the Difference Array which exceed a given minimum magnitude
may be utilized. If this minimum magnitude is the same as the aforementioned threshold
value, the count could be the number of flags set in the Difference Flags Map.
If the count significantly exceeds that which might be expected by the entry of
an intruder, the change can be declared global, and the alarm inhibited for this
Figure 3C corresponds to a global event, for example, the occurrence
of a lightning bolt, or the flash of a flashbulb. The values of the MCUs of the
Subsequent frame 320C show a marked increase in luminosity, which is reflected
in the Difference frame 330C. If the threshold value is ten, as in the prior examples,
most of the Difference Flags entries will be set to 1, as shown at 350C.
In accordance with this invention, the occurrence of a 1 in, for example, a majority
of MCUs, may be used to signal the occurrence of a global event, for which the
sounding of the alarm at 365 is inhibited. Because the Difference Map 350C contains
a majority of entries of 1, in this example, the subsequent sounding of an alarm
would be inhibited.
Thus, as presented, the assessment of the Difference Flags can be
effectively utilized to distinguish local from global changes. This distinction
can then be utilized to inhibit the sounding of a false alarm, as would be caused
in a prior art system, by the occurrence of a global change.
Alternatively from the Difference Flags approach above, the variance
of the elements within the Difference Array can be utilized to distinguish global
from local changes. It would be expected that a global change would affect all
elements similarly, and thus the variance among the magnitudes of difference would
be small. A local intrusion, however, would introduce a difference in the area
of intrusion and no difference in the other areas. Thus, a large variance would
be typical of an intrusion. These and other methods of distinguishing global changes
from localized changes in an array are common to one versed in the art, and are
within the scope of this invention.
Although the assessment of the difference array at blocks 240 and
250 could merely set an flag to inhibit the sounding of an alarm if a global change
is detected, as discussed above, a further embodiment of this invention accommodates
for the sounding of an alarm in the event of a simultaneous local and global change.
In the preferred embodiment, the effect of a global change is accommodated by raising
the threshold level for local motion detection. As shown in figure 2 and detailed
in figure 4, the detection threshold is adjusted with each frame. The average of
the magnitudes of the differences is computed as shown in steps 410 through 450
of figure 4. This average difference would be expected to be high for a global
change, and low for a local change. This average, scaled by a global sensitivity
factor, is the detection threshold which will be utilized to set the difference
flags in 250. As shown at 460, however, the detection threshold will not be set
to be less than the Threshold Minimum established at block 280, discussed above.
The global sensitivity factor may be a user definable factor, and is typically
greater than one.
Figure 3C shows the effect of an increased threshold at 355C. The
Difference frame 330C produces Difference Flags 350C if a threshold value of ten
is used, as discussed above, but the same frame 330C produces Difference Flags
355C if a threshold value of forty-eight is used. In accordance with this invention,
the average value of the MCUs of Difference frame 330C is computed at blocks 410-450
to be thirty-two. Assuming a typical global sensitivity factor of 1.5 results in
a Detection Threshold at 460 of forty-eight. As expected, the higher threshold
value results in fewer MCUs exceeding this threshold value, and hence, fewer entries
of 1 in the Difference Flags 355C.
The effectiveness of the above described dynamic detection threshold
setting, in accordance with this invention, may best be appreciated by the example
scenario, in a somewhat more general case, below.
Assume that the MCU values ranges from 0 (black image) to 100 (white
image). Further assume that the image contrast is such that the threshold minimum
is set to 10, that an intruder causes a difference of about 30 in ten percent of
the image MCUs, and that the user has set the global sensitivity to 1.50. In the
absence of a global change, assume an average difference between images of 5, as
might be caused by random factors. In the absence of an intruder, this average
difference (5) will be multiplied by the sensitivity (1.5) and compared to the
threshold minimum (10). Because the threshold minimum (10) is greater than this
product (7.5), the detection threshold is set to 10. Any MCUs having a difference
of at least 10, as might be caused by the random entry of a small animal, would
result in the corresponding difference flag to be set. Only if a cluster of set
flags is larger than the target size will an alarm be sounded at 265.
Consider the entry of an intruder, absent a global change. The intruder
will introduce a change in the average difference of about 3 (30 times 10 per cent),
resulting in a DiffAvg at 450 of 8. At 460, the detection threshold is set to the
higher of the threshold minimum (10), and the DiffAvg (8) times the GlobalSens
(1.5); that is, the detection threshold is adjusted higher, to 12, because of the
entry of the intruder. Each of the MCUs in which the intruder introduced the change
of 30 units, when compared to this threshold of 12, will result in the corresponding
difference flag being set. Assuming that the set flags corresponding to the intruder
exceed the specified target size, the alarm will be sounded, at 265.
Consider now a global change, with no intruder. The magnitude of the
difference introduced will be dependent upon the particular global change. Consider
an occurrence which causes the average difference in MCU, values to increase to
40, as computed at 450. Traditional motion detectors would sound an alarm under
these conditions, because a majority of the MCUs will exceed the threshold minimum,
and significantly large clusters of difference flags will be set. In accordance
with this invention, however, the detection threshold at 460 will be adjusted up
to a value of 60 (40 times the global sensitivity factor of 1.50). Only the locales
wherein the change is significantly greater than the average change of 40 will
have a difference flag set. Because a global change can be expected to affect the
entire image relatively uniformly, such locales can be expected to be minimal.
With few, if any, flags set, an alarm will not be sounded. Thus it is apparent that
the dynamic adjustment of threshold values in dependence upon the average change
in MCU values between frames has the desired effect of minimizing the number of
false alarms caused by global changes.
Finally, consider a global change coincident with an intruder, for
example, an intruder during a thunderstorm attempting to evade detection by moving
only when a lightning flash occurs. A traditional security system may sound an
alarm, but it may have minimal effect because the monitor will interpret it as
a false alarm triggered by the lightning. In all likelihood, the traditional security
system monitor will have turned off the motion detector after the first few lightning
induced false alarms. The preferred embodiment herein disclosed, however, will
be able to distinguish the intruder from the global changes. When local and global
changes occur, the average difference will be somewhat less than the sum of both
occurrences, because the effects of one may reduce the effects of the other. For
the ease of understanding, however, let us assume the effects are approximately
additive, such that in the example environment, most of the intruder affected MCUs
rise to almost 70 when the other MCUs rise to about 40, and produce a difference
average at 450 of about 42. The combined global and intruder changes will thus
result in a detection threshold of 63 (42 times 1.50). Since most of the intruder
affected MCUs are above this threshold minimum, the corresponding difference flags
will be set at 250, and the alarm sounded at 265. Thus it is seen that with this
preferred embodiment, local changes will be detected even when they occur coincident
with a global change. The likelihood of missing a true intrusion because of the
occurrence of global changes is thereby significantly reduced through the use of
this preferred embodiment.
Alternative techniques may be employed to adjust the threshold. For
example, the variance of the differences may be utilized to further modify the
global sensitivity factor, similar to the technique employed to adjust the threshold
minimum discussed above with regard to process 280 in figure 1. For example, if
the global occurrence has the effect of washing out most of the image, producing
little contrast, the global sensitivity in the prior example may be reduced to
1.20, so that differences which exceed the average by only 20 percent, rather than
the former 50 percent, will have their corresponding difference flag set.
Although the preferred embodiment operates by adjusting the threshold,
equivalent techniques may be employed to accomplish the same effect. For example,
the original MCU array corresponding to the image could be modified by an amount
dependent upon the average change, and conventional motion detection techniques
applied to this modified array. That is, consistent with this invention, characteristics
which can be associated with a global change can be removed from the original image.
Subsequent motion detection on this modified representation of the image results
in motion detection which is insensitive to global changes while still comprising
local motion detection capabilities.
Likewise, alternative algorithms may be employed, consistent with
the spirit and scope of this invention. For example, noting that global changes
are typically unidirectional, i.e. affecting all MCUs in either the positive or
negative direction, alternate sums of differences could be computed in 430. That
is, a sum of positive changes and a sum of negative changes. The larger of these
sums could be attributed to a global change, and the threshold could be set based
on the higher average. Or, it may be noted that global random changes, such as
trees blowing, or animals scurrying, typically result in some positive changes
and some negative changes, due to the random nature of these events. The difference
between the sum of the positive changes and the sum of the negative changes could
be utilized to adjust the detection threshold, thereby minimizing the effects of
This invention teaches that false alarms can be minimized by distinguishing
the effects of global changes from local changes. Known statistical and heuristic
techniques exist for distinguishing among effects caused by multiple causes, and
are well suited for this application. A chi-square test, for example, could be
utilized to determine which individual MCUs are significantly different from the
population of all MCUs. Or, an ANOVA (ANalysis Of Variance) test can be applied
to determine if the differences as measured by the MCU elements are consistent
with a global event or a local event, by assessing the MCUs in a row and column
fashion. In a global event, individual rows or columns should not exhibit significantly
different characteristics, as other rows or columns. An intruder, on the other
hand, will introduce a variance in the rows and columns common to the area of intrusion.
Such an ANOVA technique might best be employed, for example, in environments wherein
global changes are not unidirectional. For example, most cameras contain automatic
lens aperture adjustment for changing light conditions. When exposed to a sharp
increase in light intensity, the image of such light compensating cameras will show
a increase in the lighted areas, as well as a decrease in shaded areas.
Similarly, although for ease of implementation, the preferred embodiment
operates by comparing a single current image to a single reference image, the principles
embodied herein are equally applicable to the comparison and assessment of series
of images, to distinguish local from global changes.
The foregoing merely illustrates the principles of the invention.
It will thus be appreciated that those skilled in the art will be able to devise
various arrangements which, although not explicitly described or shown herein,
embody the principles of the invention and are thus within the scope as defined
by the claims.