JP2003169321A - Image sensor and monitoring camera apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image sensor and a monitoring camera apparatus for acquiring images having a different amount of exposure and at the same time inhibiting the number of images to be analyzed for rational image processing. <P>SOLUTION: The monitoring camera apparatus comprises a control section 101, a power supply section 102 for supplying power to each section, a lighting section 103 for lighting a monitored region, an imaging section 104 for imaging the image of the monitored region, an image-processing section 10 for analyzing the change region of images, a storage section 106, and an output section 107 for outputting the detection result via an external communication line. The control section 101 acquires two types of images having different lighting states and exposure stages by controlling the light section 103 to normal lighting and direct close lighting, and at the same time by switching the imaging section 104 to high exposure and low exposure for control. In the image-processing section 105, the brightness of these two kinds of images is appropriately corrected for analysis, thus discriminating a non-detection target such as an insect existing extremely close to the imaging section 104, and preventing an intruder to be detected originally from being detected by mistake. <P>COPYRIGHT: (C)2003,JPO

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image sensor for capturing an image by an image capturing means and analyzing the captured image.
Also, it belongs to the technical field of a surveillance camera device that captures an image of a surveillance region by an imaging means and analyzes the captured image to detect the presence of a detection target.

[0002]

2. Description of the Related Art As a conventional image sensor, a surveillance camera device is known in which a desired surveillance region is continuously photographed and the presence or absence of an intruder is determined from the photographed image. This type of surveillance camera device detects an intruder by comparing a plurality of images taken at predetermined time intervals and analyzing the change. Generally, when a plurality of images are used as an analysis target, it is necessary to capture each image in a state where the exposures based on the shutter speed and the aperture match. This is because when a plurality of images with different exposures are compared, a relative difference in the brightness value appears on the image in a specific subject, so that proper image analysis cannot be performed.

By the way, the surveillance camera device may detect insects and the like flying into the surveillance area as disturbances in addition to humans. In particular, there is a problem when an insect is present in the immediate vicinity of the surveillance camera device and the size of the insect is about human in the image. In such a situation, in order to prevent an intruder from being mistakenly detected by a non-detection target insect or the like, it is necessary to take measures to distinguish the flying insect or the like from a human. on the other hand,
The surveillance camera device is generally provided with an illumination means so that an intruder can be detected even when the surveillance area is dark. Then, in such an illumination means, it is possible to switch the amount of light and the irradiation range of the light to capture an image, and use the image to determine an insect or the like in the surveillance camera device. That is, it is possible to recognize that a bug or the like exists in the vicinity by comparing two images acquired by using the illumination of the entire surveillance area and the illumination limited to the immediate vicinity of the surveillance camera device and obtaining the difference between the two images. can do. In this case, in order to properly compare the two images, it is necessary to set the exposure amount to be constant at the time of shooting.

[0004]

However, in the above-described conventional surveillance camera device, when detecting insects and the like, the restriction of the dynamic range of the image becomes a problem. In other words, when limited illumination is provided in the immediate vicinity of the surveillance camera device, the reflected light of insects or the like may exceed the dynamic range of the image. Therefore, when using the most limited lighting,
It will be necessary to set a low exposure. In this case, in order to make the exposure amount constant for the two images as described above, it is unavoidable to set low exposure even during illumination of the entire monitoring region. Therefore, the detection target of the monitoring area will be photographed darkly,
It is not suitable for image processing to determine an intruder.

In the above conventional surveillance camera device, in order to achieve both detection of insects and expansion of the dynamic range, in addition to the image at the time of illumination of the entire surveillance area, exposure is performed when illumination is limited to the immediate vicinity. It is necessary to take a plurality of different images and combine them to perform image processing. Therefore, there is a problem in that the number of images for detecting insects and the like increases, which limits the number of images for detecting an intruder.

Therefore, the present invention has been made in view of such a problem, and pays attention to the correlation between the exposure amount at the time of photographing and the brightness value of the image, and incorporates image processing such as a logic for detecting insects and the like. Even in such a case, it is an object of the present invention to provide an image sensor and a surveillance camera device capable of performing rational image processing while suppressing the number of images used.

[0007]

In order to solve the above-mentioned problems, an image sensor according to a first aspect of the present invention is an image sensor that captures an image and an exposure that controls the exposure amount of the image sensor according to time. It is characterized by comprising an amount control means and an image processing means for correcting a difference in brightness value corresponding to a difference in the exposure amount of a photographed image and analyzing a change area based on the corrected image.

According to the present invention, the exposure amount is switched according to time in order to expand the dynamic range of the image taken by the image pickup means. Since the difference in the exposure amount appears as the difference in the brightness value of the image, the correlation of the image is corrected and the image is corrected, and then the changed region of the image is analyzed. Therefore, it is possible to appropriately analyze images when comparing images taken with different exposure amounts. At this time, if different images are acquired by changing the conditions such as the illumination state, rational image processing can be realized without increasing the number of required images.

The image sensor according to claim 2 is the image sensor according to claim 1.
In the image sensor described in above, the exposure amount control means,
The low-exposure image and the high-exposure image are alternately switched, and the image processing means corrects the brightness value of the low-exposure image with the high-exposure image as a reference.

According to the present invention, the exposure amount in two steps is controlled to be switched at the time of photographing, and the reference for correcting the difference in the brightness value corresponding to each is set to the high-exposure image. It is possible to perform highly accurate analysis in a state where there are more.

According to a third aspect of the present invention, there is provided a surveillance camera device, which comprises an image pickup means for picking up an image of a surveillance area, an illuminating means for illuminating only the immediate vicinity of the image pickup means, and the near illuminant and the image pickup. State control means for switching control between a first state in which the means is set to a predetermined exposure and a second state in which the image pickup means is set to an exposure different from the predetermined exposure without performing the nearest illumination, and the first state Image and the second
An image processing unit that corrects the difference in brightness value corresponding to the difference in the exposure amount in the image in the state of 1), analyzes the change region based on the corrected image, and determines the moving body that is the detection target in the monitoring region. And is provided.

According to the present invention, when the surveillance area is photographed by the surveillance camera device, the exposure amount for expanding the dynamic range of the image and the illumination state for detecting the non-detection target are switched according to time. Then, the images corresponding to the two states are acquired. Since the difference in the exposure amount appears as the difference in the brightness value of the image, the image is corrected in consideration of the correlation, and then the changed area of the image is analyzed to detect the moving object. Is determined. Therefore, it is possible to highly accurately determine the presence of the detection target when comparing images captured with different exposure amounts. At this time,
Since only two types of images are required when changing both the exposure state and the illumination state, rational processing can be realized without increasing the number of images. The predetermined exposure is appropriately set according to the state of the monitoring area, the monitoring purpose, and the like.

According to a fourth aspect of the present invention, in the surveillance camera apparatus according to the third aspect, the image processing means compares the image in the first state with the image in the second state. Then, the moving body affected by the closest illumination is determined as a non-detection target existing in the immediate vicinity of the imaging unit.

According to the present invention, in addition to the operation of the invention described in claim 3, the moving object is influenced by the closest illumination by comparing the two images having different exposure states and different illumination states. The non-detection target existing in the immediate vicinity of the image pickup means is determined by the analysis. Therefore, in the situation where insects or the like exist in the immediate vicinity of the surveillance camera device and the size thereof is about the same as that of a person in the image, it is possible to reliably detect this and effectively prevent erroneous detection of an intruder.

According to a fifth aspect of the present invention, in the surveillance camera device according to the fourth aspect, a saturated region in which the brightness value of an image is saturated is discriminated, and in the region excluding the saturated region from the change region. It is characterized in that the moving body is determined.

According to the present invention, when the brightness value is saturated in the image photographed by the surveillance camera device, the saturated region is discriminated and the saturated region is excluded in the above image processing.
Therefore, it is possible to perform the image processing with higher reliability by not reflecting the area where the brightness value is saturated and the reliability becomes low in the image processing.

[0017]

BEST MODE FOR CARRYING OUT THE INVENTION Preferred embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 is a functional block diagram of a surveillance camera apparatus as one embodiment to which the present invention is applied. The monitoring camera device shown in FIG. 1 includes a control unit 101, a power supply unit 102, an illumination unit 103, an imaging unit 104, an image processing unit 105, and a storage unit 1.
06, the output unit 107 is included.

In the above structure, the control unit 101 is
It is composed of a PU or the like and controls the operation of the entire surveillance camera device, and executes various determination processes and the like of the present invention according to a program stored in the storage unit 106 as described later. Further, the power supply unit 102, under the control of the control unit 101,
It plays a role of supplying electric power to each unit of the surveillance camera device, and is configured to supply AC power to the power supply unit 102 from the outside.

The illumination unit 103 is means for irradiating light for identifying an image when the monitoring area is dark. As will be described later, the illuminating unit 103 includes a normal illuminating device that radiates light widely over the entire surveillance region and a direct illuminating device that illuminates light only in the region closest to the surveillance camera device. Further, the image pickup unit 104 includes an optical system and an image pickup element such as a CCD element, and converts an analog signal corresponding to an image obtained by photographing the monitoring area into a digital image signal and outputs the digital image signal.
Digital image signals from the image pickup unit 104 are sequentially output at predetermined time intervals based on a time measuring means (not shown). In addition, as the exposure state when shooting the surveillance area,
As will be described later, it is possible to switch between a low-exposure state and a high-exposure state in order to expand the pseudo dynamic range of the image. It should be noted that the exposure state is not limited to 2 types, and 3
You may be able to switch more than the street.

The image processing section 105 is a means for processing a digital image signal from the image pickup section 104 under the control of the control section 101, and is composed of an image processing IC, an image memory and the like. The image processing unit 105 binarizes the digital image signal obtained by the image pickup unit 104, calculates parameters and attribute information necessary for the determination process described later, and
Image analysis using them is performed. Then, the processing result of the image processing unit 105 is output to the control unit 101 and is used when determining the presence or absence of an intruder. In addition, the storage unit 106
Includes, in addition to the above program, image data to be processed by the image processing unit 105 and parameters necessary for calculation,
Various types of information such as the state of the surveillance area and the operation mode of the surveillance camera device are stored so that they can be updated. Also, the output unit 10
Reference numeral 7 is a means for outputting the final detection result via an external communication line, and is notified via, for example, an alarm device or a bell.

Next, the concept of the detection method in the surveillance camera apparatus of this embodiment will be described. The binarized image extracted by the image processing unit 105 described above is calculated by taking the difference between the reference image set in advance and the captured image acquired at a predetermined time interval. Here, the reference image is
It is an image of the monitoring area in a state where no detection target (person) exists in the detection area, and is stored in advance when the monitoring camera device is initially installed. Then, when a moving object such as an intruder that does not exist in the reference image is captured in the monitoring area, the area in which the moving object exists can be identified by obtaining the changed area in which the change appears in the image at that time. It is possible to continuously extract such a change area over time and determine whether or not the moving body is an intruder based on a predetermined algorithm.

On the other hand, FIG. 2 is a diagram for explaining a situation in which there is a non-detection target insect or the like in the monitoring area. Figure 2
FIG. 2A shows a situation where insects fly near the surveillance camera device, and FIG. 2B shows a situation where insects stick to the surface of the surveillance camera device. In any situation, the insect is recognized as a moving body in the surveillance area. In this case, since the surveillance camera device and the insect are close to each other, the size in the image is about the same as that of a person, which may cause erroneous detection. In the present embodiment, a detection method capable of clearly distinguishing a non-detection target such as a bug from an original detection target by an appropriate switching control of the illumination state and the exposure state of the surveillance camera device and an image processing algorithm is adopted. ing.

Next, FIG. 3 is a diagram showing the device configuration of the surveillance camera device of this embodiment. In FIG. 3, as members constituting the surveillance camera device, a camera 201 corresponding to the imaging unit 104, a normal illumination device 202 and a closest illumination layer device 203 included in the illumination unit 103, and a transparent cover 204.
, A lens surface 205 and a prism 206 are shown.

In the above structure, the camera 201 is installed at the center of the surveillance camera device. Camera 201
Is a structure in which a lens and an image pickup element are integrated, and images the monitoring area through the lens surface 205 at a predetermined timing. Around the camera 201, the normal illumination device 202 is arranged on the far end side, and the closest illumination device 2 is arranged on the near end side.
03 are arranged, and lighting can be controlled separately. The normal lighting device 202 and the closest lighting device 20
3 is composed of, for example, a plurality of lighting LEDs. It should be noted that the normal lighting device 202 and the closest lighting device 203 are configured to be integrated with the camera 201 so as to be rotatable around an axis in the central portion of the surveillance camera device.

First, when the normal illumination device 202 is turned on, the entire monitoring area is illuminated via the transparent cover 204. In this case, the light from the normal illumination device 202 is applied to the area in the A direction in FIG. 3, but does not reach the area in the B direction in FIG. 3 which is blocked by the protruding portion of the prism 206.

On the other hand, in the state where the closest illuminating device 203 is turned on, the area closest to the camera 201 is illuminated via the lens surface 205. In this case, the light from the closest illuminating device 203 is refracted through the prism 206 and the lens surface 20.
The light is irradiated only in the area in the B direction (FIG. 3) on the upper part of the area 5, and does not reach the area outside the area.

Further, the camera 201 can switch between a low exposure state and a high exposure state by a mechanism (not shown). Generally, in a surveillance area of a surveillance camera device, a very bright portion and a very dark portion coexist, so it is necessary to artificially expand the dynamic range of the image in order to secure good image quality. Therefore, it is effective to control switching between a high-exposure state in which a very dark place can be photographed to a certain degree bright and a low-exposure state in which a very bright place can be photographed to a certain degree dark. In this embodiment,
The exposure amount of the camera 201 in the high exposure state with respect to the low exposure state is set to be eight times, for example. Note that the actual exposure amount of the camera 201 can be switched by adjusting the shutter speed.

Then, two types of images are taken by the camera 201 by combining the illumination state and the exposure state of the surveillance camera device as described above. In FIG. 4, the control conditions at the time of shooting are shown in comparison for the first image and the second image, which are the two types of images of this embodiment. First, the first image is controlled under the condition that the normal illumination device 202 is turned on and the closest illumination device 203 is turned off, and the high exposure state is obtained. Also, the second image is the normal illumination device 202.
And the closest illuminating device 203 are both turned on and controlled so as to be in a low exposure state. Then, a corrected image having a high dynamic range is generated using the two types of captured images.

As described above, in the camera device according to the present embodiment, both the exposure state and the illumination state are switched and controlled.
Acquiring a type of image. In general, while switching the lighting state for insect determination, which will be described later, independently of that,
When the exposure state is switched to expand the dynamic range, more images are needed. On the other hand, in the present embodiment, attention is focused on the correlation between the exposure amount and the brightness value of the image, and the corrected image generated from the two types of images is the analysis target. Therefore, only two types of images are required. Therefore, it is possible to reduce the capacity required for storing the image.

Next, the detection logic of this embodiment will be described with reference to FIGS. FIG. 5 is a flowchart illustrating the flow of the entire processing of the detection logic executed in the surveillance camera device. First, the current image is captured and captured by the image capturing unit 104 in a state where the setting corresponding to the first image shown in FIG. 3 is made at a predetermined timing indicated by the timing means (step S1). continue,
With the settings corresponding to the second image shown in FIG. 3,
The current image is captured and captured by the image capturing unit 104 (step S2). The first image and the second image are sequentially stored in the storage unit 106.

Next, calculation is performed using the first image in step S1 and the second image in step S2 to generate a corrected image with an expanded dynamic range (step S3). Here, in step S3, the calculation is performed for each pixel forming the image according to the following equation. P3 = P1 × α + P2 × (1-α) (1) where P1: pixel value of the first image P2: pixel value of the second image P3: pixel value of the corrected image α: 0 ≦ α ≦ 1 (Α is an experimentally obtained parameter) The corrected image obtained by the calculation of the above formula (1) can obtain a good image even when the brightness in each part in the monitoring area is significantly different. The basic idea of the detection logic based on the corrected image in this embodiment will be described later.

Next, the presence / absence of a moving object existing in the monitoring area is detected using a general method (step S4). Specifically, after comparing the above-described reference image and the corrected image to obtain the difference between them, the change area in which the change appears over time is extracted in the monitoring area, and it is determined as the moving body portion in the image. Yes (step S4). As a result of the determination in step S4, when there is no moving object in the monitoring area (step S5; NO), it is determined that no person is detected in the monitoring area (step S11). This corresponds to a normal state in which an intruder or the like is not detected.

On the other hand, as a result of the determination in step S4, when a moving object exists in the monitoring area (step S5; YE
S), the area of the moving body portion in the image is calculated, and it is determined whether or not the calculated area is within the range assumed as the size of a human (step S6). As a result, when it is determined that the area of the moving body portion is out of the human size range (step S6; NO), it can be determined that the moving body is not a person, so the process proceeds to step S11. On the other hand, when it is determined that the area of the moving body portion is within the range of human size (step S6; YE
S), the insect determination process for determining whether the moving body is an insect or the like is performed (step S7).

FIG. 6 is a flow chart for explaining the insect determination process of step S7. When the insect determination process is started, a region R1 in which the brightness value of each pixel included in the moving body portion exceeds a predetermined value is obtained by using the first image captured in step S1 as a processing target (step S21). Figure 7
An example of the region R1 obtained in the moving body portion of the first image is shown in (a). Specifically, a threshold value TH1 (for example, 254) at which the brightness value is saturated is set in advance, and an area satisfying the brightness value> TH1 among the pixels of the moving body part is obtained, and this area is determined as the area R1. And it is sufficient. This region R1 corresponds to the saturated region in the moving body portion of the first image.

Similarly, with the second image captured in step S2 as the processing target, a region R2 in which the luminance value of each pixel included in the moving body portion exceeds a predetermined value is obtained (step S22). FIG. 7B shows an example of the region R2 obtained in the moving body portion of the second image. Specifically, the threshold value TH2 (for example, 25
4) is set in advance, and an area satisfying the brightness value> TH2 among the pixels of the moving body portion may be obtained and set as the area R2. This region R2 corresponds to the saturated region in the moving body portion of the second image.

Then, with both the first image and the second image as processing targets, a region R3 that satisfies the following expression (2) in the moving body portion is obtained (step S23). Here, it is assumed that the exposure amount in the high exposure state is 8 times that in the low exposure state. In addition, in FIG. 7C, an example of the region R3 obtained by the equation (2) is shown.

Luminance value of second image × 8−luminance value of first image> TH3 (2) where TH3: predetermined threshold value (for example, 200) This equation (2) is used in the present embodiment. This is a basic expression in the insect detection logic. Hereinafter, the idea when the expression (2) is applied to insect detection will be described.

First, the brightness value of the first image and the brightness value of the second image included in the expression (2) can be expressed by the following expressions (3) and (4), respectively. Luminance value of first image = (C1 + C3) × 1 (3) Luminance value of second image = (C1 + C2 + C3) × (1/8) (4) where C1: component C2 of reflected light from the normal illumination device 202 : Component of reflected light of the closest illumination device 203 C3: component of other incident light

As described above, since the control condition shown in FIG. 4 is used, the influence (C1) of the normal lighting device 202 is as follows.
It can be seen that the effect (C2) of the direct illumination device 203 appears only in the expression (3), while it appears in both the expression (3) and the expression (4). It should be noted that in both equations (3) and (4), the influence of light arriving from other than the surveillance camera device (C
3) is assumed. Here, as shown in FIG.
Image is taken in a high-exposure state and the second image is taken in a low-exposure state, and the difference in exposure amount between them is set to 8 times as described above. Therefore, the coefficient of the equation (4) is set to 1/8 according to the correlation between the exposure amount and the brightness value of the image.

Therefore, by multiplying the equation (4) by 8 and subtracting the equation (3), the following equation (5) can be obtained. Luminance value of second image × 8−luminance value of first image = C2 (5) This equation (5) is the same as the first image and the second image when the difference in exposure amount between the two images is corrected. The result is that only the influence of the reflected light of the closest illumination device 203 is extracted. The left side of the equation (2) used in step S23 corresponds to the above equation (5). In this case, when an object such as a bug exists in the immediate vicinity of the lens surface 205 through which the light from the immediate illumination device 203 passes, the state is detected through the equation (5).

However, when the saturation of the brightness value occurs in the first image or the second image, the expression (5) is not satisfied. That is, for example, if the brightness value of each pixel can take an integer value in the range of 0 to 255, the brightness value is the maximum value of 255.
Will be saturated with. In this case, even if the amount of light incident on the image capturing unit 106 is actually a predetermined brightness value exceeding 255, the brightness value is detected as 255, and therefore the correct calculation in the above equations (3) to (5) is performed. Will not be able to do.

As described above, the ranges in which the brightness values are saturated in the first image and the second image are the region R1 in step S21 and the region R in step S22 in FIG. 6, respectively.
2 is required. Therefore, in the process of FIG. 6, the effects of saturation of the brightness value are excluded by performing steps S24 to S28 as described below.

As shown in FIG. 6, the number N1 of pixels included in the region R1 obtained in step S21 is obtained (step S
24). Similarly, the number N2 of pixels included in the region R2 obtained in step S22 but not included in the region R1 is obtained (step S25). Then, the number N3 of pixels included in the region R3 obtained in step S23 but not included in both the regions R1 and R2 is also obtained (step S2).
6). On the other hand, the number of pixels N4 included in the moving body portion determined in step S4 is obtained (step S27). Next, in order to perform the insect determination, the number of pixels N1 to N4 obtained in steps S24 to S27 is used as follows. It is determined whether or not all three expressions shown in are satisfied (step S2).
8). N1 / N4 <TH4 (6) N2 / N4 <TH5 (7) N3 / N4> TH6 (8) However, in TH4, TH5, TH6: predetermined threshold value step S28, the above (6) to (8) Judge whether all expressions are satisfied. As a result, when step S28 is affirmatively determined, the moving body in the image is determined to be a bug (step S29), and when step S28 is negatively determined, the moving body in the image is not a bug. The determination is made (step S30). In addition, as the setting of each threshold value, for example, TH4 = 0.2, TH5 = 0.2, TH6 = 0.
It may be set as 4.

Here, (6) -used in step S28
The specific meaning of the expression (8) will be described. Equation (6) is the first
When the ratio of the area occupied by the moving body portion in the image where the luminance value is saturated is large, it is considered that the reliability is low and it is not judged as a bug. Further, the expression (7) has high reliability when the ratio of the area occupied by the moving object portion in which the luminance value is not saturated in the first image but the luminance value is saturated in the second image is large. It means that it is low, and it is not judged as an insect. Further, the expression (8) is obtained when the ratio of the area occupied by the moving body portion of the portion where the luminance value is not saturated in both the first image and the second image is large, that is, the reflection of the closest illumination device 203. This means that the number of pixels in which the influence of light normally appears is large and the influence of the reflected light of the closest illumination device 203 is large. By using these as insect determination conditions, false detection due to image saturation can be avoided and a highly reliable detection logic can be realized.

Next, when the processes of steps S21 to S30 of FIG. 6 are completed, the process returns to FIG. 5 and the processes of step S8 and subsequent steps are performed. In FIG. 5, when the determination result of the process of step S7 is a bug (step S8; YES), it is determined that a non-detection target bug or the like is detected in the monitoring area (step S9). On the other hand, when the determination result of the process of step S7 is not a bug (step S8; NO), it is determined that a person (intruder) to be detected is detected in the monitoring area (step S10).

As a result of the above processing, one processing of the detection logic of this embodiment is completed. After that, the above steps S1 to S11 are repeatedly executed at predetermined time intervals. When the determination of step S9 or step S11 is made by the process of FIG. 6, it is a normal state where no intruder exists in the monitoring area, whereas step S10 is performed.
If it is determined that there is an intruder in the monitoring area, the output unit 107 reports the detection result.

Next, a modified example of the insect determination process of FIG. 6 will be described. In the insect determination process of FIG. 6, step S2
The process of selectively determining whether the insect is a bug or not is shown by 8 to S30. On the other hand, the present modification is characterized in that the “insect-likeness” is converted into a numerical value and the result of the insect determination has a range. That is, for example, the "insect-likeness" is indicated by a numerical value in the range of 0 to 1, and the "insect-likeness" is calculated so that it is maximum when the degree of insects is 1 and is minimum when the degree of insects is 1. .

FIG. 8 is a graph showing the determination part in the case of replacing steps S28 to S30 of FIG. 6 in the modified example. In this modification,
The processing of steps S21 to S27 in FIG. 6 may be performed in the same manner as described above, and can be realized by replacing the subsequent processing. In FIG. 8, three graphs, graph 1 to graph 3, are shown. In the graph 1, the horizontal axis represents N1 / N4, which is the ratio of the number of pixels N1 obtained in step S24 and the number of pixels N4 obtained in step S27. Graph 2 is
The number of pixels N2 obtained in step S25 and the number of pixels N4 described above
The ratio of N2 / N4 is plotted on the horizontal axis. Graph 3
Indicates the ratio N3 / N4, which is the ratio of the number of pixels N3 obtained in step S26 and the number of pixels N4 described above, on the horizontal axis.

For each of the parameters N1 / N4, N2 / N4 and N3 / N4 of the three graphs, an appropriate graph shape was obtained after experimentally examining the correlation with "insect-likeness". Accordingly, the value B1 on the vertical axis of graph 1, the value B2 on the vertical axis of graph 2, and the value B3 on the vertical axis of graph 3 can be determined based on the parameter of the horizontal axis of each graph. Finally, the “insect-likeness” B is calculated by taking the product of the vertical axes of the three graphs and B = B1 × B2 × B3. For example,
N1 / N4 = 0.2, N2 / N4 = 0.2, N3 / N4
= 0.15, B based on Graph 1 to Graph 3
Since 1 = 1, B2 = 1, and B3 = 0.5 are obtained, "insect-likeness" B == 0.5.

Since the "insect-likeness" determined in this way has a wide range of numerical values, it is necessary to apply various determinations so as to finally detect the presence of insects. For example, separately
After determining the "personality" of the moving body, compare this with "insect-likeness", and if "insect-likeness" is greater,
You should judge it as a bug, not a person. Alternatively, in order to suppress the instantaneous fluctuation of the value, a value obtained by temporally accumulating the “insect-likeness” may be used in the determination.

In the above embodiments, the case where the present invention is applied to the surveillance camera device has been described, but the present invention is not limited to this, and the present invention can be widely applied to image sensors for various purposes. In this case, if the image sensor has a configuration in which the exposure amount for the image pickup unit is switched and controlled, and the brightness value is corrected as described above to perform image processing,
The present invention can be applied irrespective of the presence or absence of illumination control and detection logic for non-detection targets.

[0053]

As described above, according to the present invention, the exposure amount is switched and controlled at the time of shooting, the difference in the brightness value corresponding to the difference in the exposure amount of the image is corrected, and the change is made based on the corrected image. Since the area is analyzed, it is possible to realize an image sensor and a surveillance camera device that reduce the number of images and perform rational image processing.

[Brief description of drawings]

FIG. 1 is a functional block diagram of a surveillance camera device as one embodiment to which the present invention is applied.

FIG. 2 is a diagram illustrating a situation in which a non-detection target insect or the like exists in a monitoring area.

FIG. 3 is a diagram showing a device configuration of a surveillance camera device of the present embodiment.

FIG. 4 is a diagram showing, in comparison, control conditions at the time of shooting for the first image and the second image in the present embodiment.

FIG. 5 is a flowchart illustrating the flow of the entire processing of the detection logic of this embodiment.

FIG. 6 is a flowchart illustrating the insect determination process of step S7 of FIG. 5 in the detection logic of this embodiment.

7 is a region R obtained in steps S21 to S23 of FIG.
It is a figure which shows the example of 1-R3.

FIG. 8 is a graph showing a determination part relating to a modified example of the present embodiment.

[Explanation of symbols]

101 ... Control unit 102 ... power supply unit 103 ... Illumination unit 104 ... Imaging unit 105 ... Image processing unit 106 ... Storage unit 107 ... Output unit 201 ... camera 202 ... Ordinary lighting device 203 ... Nearest illumination device 204 ... Transparent cover 205 ... Lens surface 206 ... Prism

─────────────────────────────────────────────────── ─── Continuation of front page (51) Int.Cl. ⁷ Identification code FI theme code (reference) G08B 13/196 G08B 13/196 H04N 5/225 H04N 5/225 C F term (reference) 2H002 DB25 EB09 5C022 AA05 AB01 AB15 AC41 AC69 5C054 AA01 CA04 CC02 CH02 EA01 ED17 FC01 FC05 GB01 GB12 HA18 5C084 AA02 AA07 BB05 CC17 DD12 EE02 FF03 FF10 GG43 GG57 GG78

Claims (5)

[Claims] 1. An image pickup means for picking up an image, an exposure amount control means for switching the exposure amount of the image pickup means according to time, and a difference in brightness value corresponding to the difference in the exposure amount of the picked-up image. And an image processing unit that corrects the change area and analyzes the changed region based on the corrected image. 2. The exposure amount control means alternately switches between two steps of low exposure and high exposure, and the image processing means corrects the brightness value of the low exposure image with reference to the high exposure image. The image sensor according to claim 1, wherein the image sensor is an image sensor. 3. An image pickup means for picking up an image of a monitoring area, an illuminating means for illuminating only the immediate vicinity of the image pickup means, and a first illuminating means for illuminating the image in the immediate vicinity of the image pickup means. State control means for switching control between a state and a second state in which the image pickup means has an exposure different from the predetermined exposure without performing the closest illumination; and an image in the first state and a second state. An image processing unit that corrects a difference in brightness value corresponding to the difference in the exposure amount in the image, analyzes a change region based on the corrected image, and determines a moving object that is a detection target in the monitoring region; A surveillance camera device comprising: 4. The image processing means compares the image in the first state with the image in the second state, and a moving object affected by the closest illumination is present in the immediate vicinity of the imaging means. The surveillance camera device according to claim 3, wherein the surveillance camera device is determined as a non-detection target. 5. The surveillance camera apparatus according to claim 4, wherein a saturated region in which the brightness value of the image is saturated is determined, and the moving object is determined in a region excluding the saturated region from the change region. .