JP2007022360A - Vehicular security system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a vehicular security system capable of spontaneously detecting abnormality of a monitoring camera from abnormality in a shot image, and informing a user of failure. <P>SOLUTION: The vehicular security system 1 comprises the monitoring camera 5 shooting a predetermined monitoring view field in a vehicle, and a monitoring information output portion 8 outputting monitoring information on the basis of the shot image of the monitoring camera 5. The vehicular security system 1 also comprises a failure diagnostic shooting controlling means 22b ordering shooting of a failure diagnostic image to the monitoring view field at predetermined timing which is 2 or more, a failure determining means 22b comparing failure diagnostic images 21a to 21d shot by the monitoring camera 5 at each timing and carrying out failure determination of the monitoring camera 5 on the basis of the compared result, and a failure determination result output means 8 outputting a failure determination result by the failure determining means 22b. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a vehicular security system using a surveillance camera.

JP 11-328544 A Japanese Patent Laid-Open No. 10-097691 Japanese Patent Laid-Open No. 08-063688 Japanese Patent Laid-Open No. 10-145774

  2. Description of the Related Art Conventionally, various vehicular security systems have been proposed in which a surveillance camera is mounted in a vehicle room and an intruder can be photographed by the surveillance camera when there is something that enters the room. For example, Patent Document 1 discloses a system in which a vehicle user sets a monitoring state at the time of parking, and then, when various sensors mounted on the vehicle detect an abnormality of the vehicle, the inside of the vehicle is photographed by the monitoring camera. Yes. Further, Patent Document 2 compares a face image of a person taken by a surveillance camera with a face image of a user registered in advance, and if a face image other than a registered person is recognized, a theft prevention device is disclosed. Techniques for operating are disclosed. Further, Patent Documents 3 and 4 disclose a system that detects that there is an intrusion abnormality when there is some change in the image of the field of view being monitored and warns.

  In the above prior art, the surveillance camera performs photographing for the purpose of specifying a suspicious person when an abnormality such as the occurrence of an intruder is detected. Therefore, even if the camera or the image processing circuit associated with it is out of order, there is no means for confirming and informing this in advance, and intruders can be photographed in the event of an emergency. There was a problem that could not be done. In addition, when an abnormality caused by a failure occurs in the captured image, the captured image of the camera can be displayed on a display such as a car navigation system screen and can be visually confirmed by the user, but it is troublesome to confirm each time. There is an uncertain problem.

  An object of the present invention is to provide a vehicular security system that can spontaneously detect an abnormality of a monitoring camera from an abnormality of a captured image and can notify a user of a failure.

Means for Solving the Problems and Effects of the Invention

In order to solve the above problems, a vehicle security system according to the present invention includes:
Based on a surveillance camera having a surveillance camera for photographing a predetermined surveillance field of view in a vehicle compartment, an image processing circuit for converting a video signal from the surveillance camera into photographed image data, and an image taken by the surveillance camera A vehicle security system comprising a monitoring information output unit for outputting monitoring information,
A failure diagnosis imaging control means for instructing the monitoring camera to capture a failure diagnosis image with respect to the monitoring field of view at two or more predetermined timings;
A failure determination means for comparing failure diagnosis images taken by the monitoring camera at each timing, and determining a failure of the monitoring camera based on the comparison result;
Failure determination result output means for outputting a failure determination result by the failure determination means.

  According to the configuration of the present invention described above, a failure diagnosis image is taken by the monitoring camera at two or more different timings separately from the in-vehicle monitoring image. Then, by comparing these fault diagnosis images, if the camera is normal, it is possible to capture changes that should originally appear on those fault diagnosis images, or, conversely, changes that are not possible. It is possible to easily determine whether or not there is an abnormality in the monitoring camera by comparing the diagnostic images.

  The failure diagnosis shooting control means causes the monitoring camera to take a failure diagnosis image at two timings in which it is known in advance that a difference in image content occurs when an image of the monitoring field of view is normally shot. It can be. In this case, the failure diagnosing means can determine that the surveillance camera is broken when there is no difference between the two photographed images for failure diagnosis (shooting itself is 3 timings or more). And it is sufficient to use failure diagnosis images taken at least at two timings). By selecting two timings that are highly likely to cause differences in image content and taking images for failure diagnosis, if there is no difference in the resulting failure diagnosis images, the surveillance camera will fail. The state can be recognized with high probability.

  Next, in contrast to the above, the failure diagnosis imaging control means, in contrast to the above, has two timings in which it is known in advance that there is no difference in image content when an image of the monitoring visual field is normally captured. It is also possible to take an image for failure diagnosis at. In this case, the failure diagnosis unit can determine that the monitoring camera is broken when there is a difference between the two photographed images for failure diagnosis. For example, when an abnormality occurs in the image processing circuit of the surveillance camera, a video signal that is irrelevant to the field of view and has no meaning may be generated indefinitely. If shooting is performed in such a state, the above-mentioned meaningless change in the video signal is captured as it is, so if shooting is performed at different timings, two “images” that are different in shape can be obtained. It will be. Therefore, if you select a highly probable field of view that does not cause a difference in image content and take a fault diagnosis image at two timings, you should be able to obtain an image that is essentially not different. If it has occurred, it can be determined with high probability that such a failure has occurred in the surveillance camera.

  It is also possible to combine the above two failure determination methods. In this case, the shooting control means for failure determination failure diagnosis is the first set of failure diagnosis images at two timings that are known to cause a difference in image content in the first monitoring field of view with respect to the monitoring camera. In the second monitoring visual field different from the first monitoring visual field, when the image of the monitoring visual field is normally captured, there are two timings in which it is known in advance that there is no difference in the image content. Thus, the second set of failure diagnosis images can be taken. The failure diagnosis unit determines that the monitoring camera is normal when there is a difference between the first set of failure diagnosis images and when there is no difference between the second set of failure diagnosis images. It is supposed to be. Surveillance camera abnormalities (failures) may occur when the entire image turns white or black due to the interruption of the video signal, or when a single-color frame image called a blue background is displayed instead of when the signal is abnormal. If the next image has arrived but the previous image captured in the memory continues to remain uncleared, the type of abnormality (hereinafter referred to as the first type abnormality) and level There are two types of abnormalities (hereinafter referred to as “second-type abnormalities”) in which the image state changes every moment, such as when an abnormal signal current that changes is flowing. According to the above method, if any of these two types of abnormalities occur, it is possible to accurately determine the failure, and only if it does not fall under any of these, In addition, it is possible to further increase the accuracy of the monitoring camera abnormality / normality determination.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
FIG. 1 is a schematic block diagram showing an example of a vehicle security system of the present invention. In the vehicle security system 1, a monitoring camera 5, an intrusion sensor 6, a vehicle state detection unit 7, and a display unit (comprising an LCD or the like) 8 are connected to a control device 2. The control device 2 is mainly composed of a microcomputer 3, and the display unit 8 and the monitoring camera 5 are connected to the control device 2. The surveillance camera 5 includes a camera body 5M having an optical system and an image sensor that detects an image formed by the optical system, and a decoder IC 9 that converts an analog image signal from the camera body 5M into digital image data. Is provided with a first-in first-out (FIFO) memory 10 that captures and outputs pixel data in time series, and an image capture unit 4 that includes an SRAM 11 that stores image pixel data from the FIFO memory for each frame. .

  FIG. 2 shows a more detailed block diagram. The main microcomputer 3 is a CPU 20, a RAM 21, a ROM 22 (in this embodiment, constituted by a ROM whose contents can be electrically rewritten such as a flash memory) and an input / output unit 23 connected by a bus. The input / output unit 23 includes the monitoring camera 5, the strobe 14 (and its drive unit 24) serving as an auxiliary light source for photographing the monitoring camera 5, the intrusion sensor 6, the vehicle state detection unit 7, and a display The unit 8 (which may also be used as the display unit of the car navigation system), the clock 25, and the security operation unit 13 are connected. In this embodiment, the vehicle state detection unit 7 includes a door lock sensor 7a, a door courtesy switch 7b that detects opening and closing of the door, an ignition switch 7c, a shift lever position detection unit 7d, a vehicle speed sensor 7e, and the like. The security operation unit 13 includes, for example, an alarm 13a that outputs an alarm sound and a communication unit (DCM) 12 that wirelessly communicates with a management center outside the vehicle.

  Hereinafter, the basic operation of the security system 1 will be described. This operation control is realized by executing the security control program 22 a stored in the ROM 22. The security operation unit 13 is set when the vehicle is parked. Specifically, in the vehicle state detection unit 7, when the shift lever position detection unit 7d detects the parking position and the ignition switch 7c is OFF, the microcomputer 3 indicates that the vehicle is in the “parking state”. Is determined. Then, when the intrusion sensor 6 is not detecting a person, the door courtesy switch 7b is turned off (door closed), and the door lock sensor 7a detects the door lock state, the inside of the vehicle is in an “unmanned state”. judge. When the “unmanned state” is established together with the “parking state”, the microcomputer 2 instructs the security operation unit 13 to set the security.

  In this security set state, when a bandit enters the vehicle and the intrusion sensor 6 detects this, the microcomputer 2 issues a command to the strobe drive unit 24 to turn on the strobe 14, while the surveillance camera 5 determines in advance in the vehicle. The observed surveillance field is photographed. For example, as shown in FIG. 3, the monitoring camera 5 is attached together with the strobe 14 so that the inside of the vehicle can be photographed from the front glass 37 side, such as above the rearview mirror 31. As shown in FIG. 4, the surveillance camera 5 captures an in-vehicle monitoring image in such a manner that the driver DRV seated in the driver's seat and the space on the passenger seat side and the rear side are also included in the field of view. The captured monitoring image is stored in the monitoring image memory 22c of FIG. 2 and can be displayed and output on the display unit 8 by inputting an output command from the operation unit 15. Then, the security operation unit 13 detects an intrusion abnormality of the bandit, outputs an alarm sound from the alarm 13a, and wirelessly reports the occurrence of the abnormality to the management center by the communication unit 12. In addition, you may make it transmit the monitoring image which caught the bandit according to the management center.

Next, the vehicle security system 1 of the present invention is equipped with the following failure diagnosis function of the monitoring camera 5. A failure diagnosis program 22b installed in the ROM 22 is a means for realizing the failure diagnosis function. The failure diagnosis program 22b implements the following means.
Failure diagnosis imaging control means: commands the monitoring camera 5 to capture the failure diagnosis images A, A ′, B, and B ′ with respect to the monitoring field of view at two or more predetermined timings. The diagnostic images are acquired from the image capture unit 4 and stored in the image memories 21a to 21d of the RAM 21).
Failure determination means: The failure diagnosis images (A and A ′ or B and B ′) taken by the monitoring camera 5 at each timing are compared, and the failure determination of the monitoring camera 5 is performed based on the comparison result.
Failure determination result output means: Outputs the failure determination result by the failure determination means. The display unit 8 can be used as an output destination.

  As described above, the surveillance camera 5 originally captures the interior of the vehicle when the intrusion sensor 6 provided in the vehicle detects an intruder (bandit) during the security set. However, for the failure diagnosis images A, A ′, B, and B ′, the surveillance camera 5 detects that a special intruder is detected by the intrusion sensor 6 at a shooting timing that is separately defined as described later. Even if it is not in a state, it takes a picture. Then, if these fault diagnosis images A, A ′, B, and B ′ are compared, if the camera is normal, changes that should originally appear on the fault diagnosis images (for example, A and A ′), or On the other hand, it is possible to capture changes that do not originally appear on the failure diagnosis images (for example, B and B ′), and easily determine whether there is an abnormality in the monitoring camera 5 based on this. can do.

  Specifically, two methods can be considered. In the first method, two timings that are known in advance to cause a difference in image contents when an image of a monitoring field of view is normally captured are determined as the imaging timings of the fault diagnosis images A and A ′. That's it. In this case, when there is no difference between the two photographed failure diagnosis images A and A ′, it can be determined that the surveillance camera 5 is malfunctioning.

  In the above case, one of two timings for capturing the failure diagnosis images A and A ′ can be set while the vehicle is parked, and the other can be set while the vehicle is running. In this case, a visual field including the driver's seat 32 of the vehicle can be selected as a visual field for monitoring the failure diagnosis images A and A 'as shown in FIG. As shown in FIG. 5, the driver's seat 32 of the vehicle is normally unattended during parking, and conversely, as shown in FIG. 4, the driver DRV is always seated while the vehicle is running. As shown in FIG. 6, the images are taken as failure diagnosis images A and A ′. Then, if the vehicle is parked, the driver DRV is not captured, and conversely, if the vehicle is traveling, the driver DRV is always captured, so there is a very large difference between the two images. Accordingly, when there is no significant difference between the two failure diagnosis images 21a to 21d, it can be determined with certainty that the monitoring camera 5 is in failure. In this failure mode, when the video signal is interrupted, the entire image becomes completely white or completely black, or a single color (for example, blue) frame image called a blue back that is displayed instead of when the signal is abnormal is displayed. Alternatively, as shown in FIG. 7, the case where the next image has arrived but the previous image captured in the memory (SRAM 11 in FIG. 1) remains without being cleared can be exemplified. Note that if shooting is performed at night during parking, the probability of shooting in an unattended state increases. The shooting time can be set from the input unit provided in the operation unit 15 in FIG. 2, and the time is managed by the clock 25.

  As for the setting state of image pixels, in the case of a color or gray scale image, a state of 2 bits or more is assigned to each pixel. There may be subtle differences in pixel settings. In order to prevent misjudgment based on this difference, for example, when comparing two failure diagnosis images, a method of binarizing the images with an appropriate threshold, or a setting value between corresponding pixels between images Not only when the sum of absolute difference values is zero, but also when the difference absolute value is within a certain allowable range, a method for determining image matching can be exemplified (these methods are well known in the field of image processing). Therefore, detailed description is omitted).

  FIG. 8 is a flowchart showing an example of the flow of the failure diagnosis process in the above case (this process is repeatedly executed at regular time intervals: the same applies to the flowcharts of other figures). . In S1, it is determined whether or not the vehicle is parked (in this embodiment, whether or not the security set is being performed). If Yes, the process proceeds to S2, and whether or not the first failure diagnosis image A has already been taken. Check for no. If the image has been shot, the process of the cycle is terminated. If shooting has not yet been performed, the process proceeds to S3, where an image A (bottom of FIG. 6) is shot, and the processing of the cycle ends.

  On the other hand, in the case of No in S1, the process proceeds to S10 to check whether or not the fault diagnosis image A (in the security set) has already been taken. If No, the process of the cycle is terminated. On the other hand, if Yes, the process proceeds to S4 in order to capture the next failure diagnosis image A 'while traveling. Then, whether or not the vehicle is traveling is checked in S4 with reference to, for example, the detection state of the vehicle speed sensor 7e in FIG. If No, the process of the cycle is terminated. On the other hand, if Yes, the process proceeds to S5, and it is checked whether or not the failure diagnosis image A 'has already been taken. If Yes, the process of the cycle is terminated, and if No, the process proceeds to S6 and the failure diagnosis image A 'is captured. Then, in S8, the failure diagnosis image A (in the security set) and the failure diagnosis image A ′ (in the traveling state) are compared, and if they match, the monitoring camera 5 is abnormal. Is output on the display unit 8 of FIG. Further, if the two do not match in S8, it is determined as normal and the processing of the cycle is terminated without doing anything.

  In the process of FIG. 8, the failure diagnosis imaging control means causes the monitoring camera 5 to capture the first failure diagnosis image A while the vehicle is parked, and then the second failure diagnosis image while the vehicle is traveling. The image A ′ was taken. That is, since the acquisition of the second failure diagnosis image A ′ that enables image comparison is performed while the vehicle is traveling, the failure diagnosis means performs the first failure diagnosis while the vehicle is traveling (following). The abnormality determination can be quickly performed by comparing the image A and the second failure diagnosis image A ′. In this case, as shown in the upper part of FIG. 6, since the driver DRV (user) of the vehicle exists in the vehicle, when it is determined that there is a failure based on the comparison result, the determination output provided in the vehicle is a failure determination. If the result is output to the result output means 8, the occurrence of the abnormality can be notified to the user quickly and reliably.

  On the other hand, the failure diagnosis photographing control means causes the monitoring camera 5 to photograph the first failure diagnosis image A ′ while the vehicle is traveling, and then to photograph the second failure diagnosis image A while the vehicle is parked. Can be. In this case, since the acquisition of the second failure diagnosis image A that enables image comparison is performed while the vehicle is parked, the failure diagnosis means performs the first failure diagnosis while the vehicle is parked (following). By comparing the image A ′ for use with the second failure diagnosis image A, the abnormality determination can be performed quickly. In this case, as shown in the lower part of FIG. 6, it is highly likely that the driver (user) of the vehicle is not already in the vehicle and has left the vicinity of the vehicle after parking the vehicle. Therefore, when it is determined that there is a failure based on the comparison result, as shown in FIG. 9, the determination output is transmitted to the wireless portable terminal 42 serving as the failure determination result output means carried by the user of the vehicle M (via the data relay station 41). If wireless transmission is performed, it is possible to promptly and reliably notify the user of the occurrence of an abnormality. In particular, a user who goes to his / her home or office after parking will leave the vehicle unattended for a long time, and in response to the arrival of a scene where the operation of such a security function is most expected, The effect of being able to notify the user is extremely great.

  FIG. 10 is a flowchart showing an example of a flow related to the failure diagnosis process in the above case (this process is executed repeatedly at regular time intervals). In S51, it is determined whether or not the vehicle is traveling. If Yes, the process proceeds to S52 to check whether or not the first failure diagnosis image A 'has already been taken. If the image has been shot, the process of the cycle is terminated. If shooting has not yet been performed, the process proceeds to S53, where the image A '(upper part of FIG. 6) is shot, and the processing of the cycle ends.

  On the other hand, in the case of No in S51, the process proceeds to S60, and it is checked whether or not the failure diagnosis image A ′ (during traveling) has already been taken. If No, the process of the cycle is terminated. On the other hand, if Yes, the process proceeds to S54 in order to capture the next failure diagnosis image A during parking (in the present embodiment, during the security set). In step S54, it is confirmed whether the security set is in progress. If No, the process of the cycle is terminated. On the other hand, if Yes, the process proceeds to S55, and it is checked whether or not the fault diagnosis image A has already been taken. If Yes, the process of the cycle is terminated, and if No, the process proceeds to S56 and the failure diagnosis image A is taken. Then, in S58, the failure diagnosis image A (in the security set) is compared with the failure diagnosis image A ′ (in the traveling state), and if they match, the surveillance camera 5 is abnormal. Is output on the display unit 8 of FIG. Also, if the two do not match in S58, it is determined as normal and the processing of the cycle is terminated without doing anything.

  Next, it is possible to set both of the two timings for capturing the failure diagnosis image while the vehicle is running. Also in this case, as shown in FIG. 4, it is possible to select a visual field α including the driver's seat 32 of the vehicle as a monitoring visual field for photographing the failure diagnosis images A ′ and A ″. Thus, the driver DRV seated in the driver's seat should have certain movements such as changing the posture and face direction and moving his eyes even while driving. If the fault diagnosis images A ′ and A ″ are taken at an appropriate interval between the two timings, there is a high possibility that a clear difference will occur between the two images A ′ and A ″ due to the above-described movement of the driver DRV. Therefore, when there is no significant difference between the two failure diagnosis images A ′ and A ″, it can be determined with high probability that the monitoring camera 5 is in failure. In particular, as shown in FIG. 11, when a driver DRV is seated on the driver's seat 32 as a monitoring field for photographing the failure diagnosis images A ′ and A ″, a field including the face F is selected. The accuracy of failure determination can be further increased.

  In addition, when both timings are set while the vehicle is traveling, a field of view for photographing the scenery outside the window of the vehicle is selected as a field of view for photographing a failure diagnosis image, as shown in FIG. Even in this case, the same effect can be achieved. FIG. 4 shows an example of the field of view that can capture the scenery outside the window. The field of view γ is set at the side window position of the rear seat, and the field of view δ is set at the rear window position.

  FIG. 13 is a flowchart showing the flow of processing in this case. In S101, it is confirmed that the vehicle is traveling. If No, the process of the cycle is terminated. On the other hand, if Yes, the process proceeds to S102, and a fault diagnosis image (for example, A 'in FIG. 11 or C' in FIG. 12) is taken. Then, after waiting for a certain time in S103, the process proceeds to S104, and the next failure diagnosis image (for example, A ″ in FIG. 11 or C ″ in FIG. 12) is taken. Then, in S105, two failure diagnosis images (A ′ and A ″ or C ′ and C ″) are compared, and if they match, a message notifying that the monitoring camera 5 is abnormal is shown in FIG. Display on the display unit 8. Further, if the two do not match in S106, it is determined to be normal and the processing of the cycle is terminated without doing anything.

  Next, contrary to the above, the failure diagnosis imaging control means, in contrast to the above, has two timings in which it is known in advance that there is no difference in image content when an image of the monitoring field of view is normally captured. Thus, the failure diagnosis images 21a to 21d may be photographed. In this case, as shown in FIG. 14, the failure diagnosis means can determine that the monitoring camera 5 has failed when there is a difference between the two photographed failure diagnosis images B and B ′. it can. The field of view for photographing the failure diagnosis images B and B ′ is determined in advance at a position that is not obstructed by the vehicle occupant among the stationary members 33 that are fixedly present inside the traveling vehicle. It is possible to select the field of view in which the reference member 33 is photographed. As long as the passenger DRV does not take an unnatural and unreasonable posture in the vehicle, there is a considerable field of view β in which a part of the body of the passenger DRV is not reflected, and a stationary member existing in such a field of view β The (reference member) 33 always produces the same image as long as the position of the monitoring camera 5 does not change. Therefore, by using this, it is possible to determine with high probability whether or not the surveillance camera 5 is out of order. As an example of such a reference member 33, a pillar 33 that forms a part of a window frame of a vehicle can be exemplified, but the reference member 33 is not limited thereto.

  As shown in FIG. 15, the reference member 33 such as the above-described pillar also has a photographed image when the user wears ornaments such as a mascot or amulet (hereinafter collectively referred to as an attachment OM). Can still change (B and B ′). However, since the base is the stationary member 33, there is no continuous movement like a passenger or landscape, and there is little continuous change in the captured image (that is, the wearing object OM is once worn). If this happens, the content of the still image that will be captured thereafter will remain unchanged (B ′ and B ″).) Therefore, the imaging control means for fault diagnosis was captured with respect to the monitoring camera 5 at the first timing. If the failure diagnosis image B and the failure diagnosis image B ′ taken at the second timing after that do not match, the failure diagnosis is performed at one or more times after the second timing. The image B ″ is additionally photographed, and the failure determination unit 22b determines whether the failure diagnosis images B ′ and B ″ captured at the adjacent timings after the second timing coincide with each other. Shall perform Can. Thus, by detecting the sudden image changes due to mounting thereof OM, it is possible to prevent a problem that erroneous determination that failure.

  In particular, when the first timing is set while the vehicle is parked and the second timing and additional shooting timing are set while the vehicle is traveling, the effect of the additional shooting as described above is remarkable. That is, in many cases, the user procures the above-mentioned attachment OM during parking, returns to the vehicle, attaches the attachment OM, and directly shifts to driving (running). In this case, the wearing object OM that was not shown in the figure is shown in the image B ′ taken during the traveling, and there is a clear difference between the two images B and B ′. However, if the third shot is taken again while driving, the ornament will also appear in the image B ″. For example, compare the second and third images B ′ and B ″. Thus, it is possible to determine whether the image is unchanged (that is, normal).

  FIG. 16 shows a flowchart in this case (here, the first image is taken during parking, and the second image is taken while traveling. This sequence is shown in FIG. As well as reverse). In S1, it is determined whether or not the vehicle is parked (in this embodiment, whether or not the security set is being performed). If Yes, the process proceeds to S2 ′, and the first failure diagnosis image B has already been taken. Check whether there is any. If the image has been shot, the process of the cycle is terminated. If shooting has not yet been performed, the process proceeds to S3 ', where the image B (upper part of FIG. 15) is shot, and the processing of this cycle is completed.

  On the other hand, in the case of No in S1, the process proceeds to S10 'to check whether or not the failure diagnosis image B (the one in the security set) has already been taken. If No, the process of the cycle is terminated. On the other hand, if Yes, the process proceeds to S4 to capture the next failure diagnosis image B 'while traveling. Then, whether or not the vehicle is traveling is checked in S4 with reference to, for example, the detection state of the vehicle speed sensor 7e in FIG. If No, the process of the cycle is terminated. On the other hand, if Yes, the process proceeds to S5 'to check whether or not the failure diagnosis image B' has already been taken. If Yes, the processing of the cycle is terminated, and if No, the process proceeds to S6 'and the failure diagnosis image B' is captured. Then, in S8 ', the failure diagnosis image B (in the security set) is compared with the failure diagnosis image B' (in the traveling state). The processing of the cycle is finished without On the other hand, if they do not match in S8 ′, the process proceeds to S12, and the third image B ″ (lower part of FIG. 15) is photographed and compared with the second image B ′ in S11. If it does not match, the message indicating that the monitoring camera 5 is abnormal is displayed and output on the display unit 8 in FIG.

  It is also possible to combine the above two failure determination methods. In this case, the imaging control means for failure diagnosis first monitors the monitoring camera 5 at two timings that are known in advance to cause a difference in image contents in the first monitoring field of view α as shown in FIG. When the images of the monitoring field of view are normally captured in the second monitoring field of view β different from the first monitoring field of view α, the failure diagnosis images A and A ′ (FIG. 6) of A second set of failure diagnosis images B and B ′ (FIG. 14) is photographed at two timings that are known to cause no difference in content. The failure diagnosis means monitors when there is a difference between the first set of failure diagnosis images A and A ′ and there is no difference between the second set of failure diagnosis images B and B ′. It is determined that the camera 5 is normal. The first monitoring field of view α and the second monitoring field of view β are set so as to form different parts of the same photographing field of view of the monitoring camera 5, and the first set of failure diagnosis images A and A ′ and the first monitoring field of view α are set. Two sets of corresponding failure diagnosis images B and B ′ at respective timings can be simultaneously photographed by the monitoring camera 5. If it does in this way, the image A (A ') of the 1st monitoring visual field (alpha) for determining the presence or absence of 1st type abnormality, and the image of the 2nd monitoring visual field (beta) for determining the presence or absence of 2nd type abnormality B (B ') can be obtained at one time for each timing, and it is efficient, and there is no difference in the shooting time for the two fields of view, so the influence of disturbance such as sudden outside light It becomes difficult to receive.

  FIG. 17 shows a flowchart in this case (the first image is taken during parking and the second image is taken while traveling. This order is the same as in FIG. May be reversed). In S1, it is determined whether or not the vehicle is parked (in this embodiment, whether or not the security is set). If Yes, the process proceeds to S2 ", and the first failure diagnosis images A and B have already been taken. If the image has been shot, the processing of the cycle is terminated. If the shooting has not been completed, the process proceeds to S3 "to take images A and B, and the processing of the cycle is completed.

  On the other hand, in the case of No in S1, the process proceeds to S10 "to check whether or not failure diagnosis images A and B (in the security set) have already been taken. If Yes, the process proceeds to S4 to capture the next failure diagnosis images A ′ and B ′ during traveling, and whether or not the vehicle is traveling in S4, for example, is detected by the vehicle speed sensor 7e in FIG. If the answer is No, the process of the cycle is terminated. On the other hand, if Yes, the process proceeds to S5 "to check whether the fault diagnosis images A 'and B' have already been taken. . If Yes, the processing of the cycle is terminated, and if No, the process proceeds to S6 "and the failure diagnosis images A 'and B' are photographed. In S8, the failure diagnosis image A and the failure diagnosis image A '. If the two do not match, the process further proceeds to S8 ′ to compare the fault diagnosis image B with the fault diagnosis image B ′, where the fault diagnosis image A and the fault diagnosis image A ′ do not match. Only when there is a failure diagnosis image B and the failure diagnosis image B ′ match, it is determined to be normal and the processing of the cycle is terminated without doing anything. A message notifying that the camera 5 is abnormal is displayed on the display unit 8 in FIG.

  The normality / abnormality of the bus state connecting the decoder IC 9 and the FIFO memory 10 of the monitoring camera 5 in FIG. 1 is confirmed by monitoring the terminal voltage of the bus with a dedicated device. However, this method requires a separate voltage monitoring device, and if the image changes due to the bus condition, etc., the change cannot be detected by the voltage alone, so it is determined whether it is really normal. It is difficult. Therefore, if certain inspection image data is transmitted from the decoder IC 9 to the FIFO memory 10 and input to the microcomputer 3 via the SRAM 11, the transmitted images are captured at regular intervals and image comparison is performed. Based on the comparison result, whether or not an abnormality has occurred can be easily and accurately determined without using a dedicated device. For example, when a change occurs in an image due to a bus, the above comparison result does not match, so that an abnormality determination can be made. For the inspection image data, it is effective to adopt a single-color frame image such as the above-described blue back because it is easy to catch image changes.

The block diagram which shows schematic structure of the security system for vehicles of this invention. The block diagram which shows the detail of FIG. The schematic diagram which shows the example of installation of the monitoring camera in the security system for vehicles of FIG. The schematic diagram which shows the example of a setting of the imaging | photography visual field of the image for a fault diagnosis in driving | running | working. The schematic diagram which shows the example of a setting of the imaging | photography visual field of the image for failure diagnosis in parking. The schematic diagram which shows the 1st imaging | photography example of the image for failure diagnosis. The schematic diagram which shows the 2nd imaging example of the image for failure diagnosis. The flowchart which shows the 1st example of a failure determination process. The schematic diagram which shows the system structural example which outputs a failure determination result by radio | wireless. The flowchart which shows the 2nd example of a failure determination process. The schematic diagram which shows the 3rd imaging example of the image for failure diagnosis. The schematic diagram which shows the 4th example of imaging | photography of the image for failure diagnosis. The flowchart which shows the 3rd example of a failure determination process. The schematic diagram which shows the 5th example of imaging | photography of the image for failure diagnosis. The schematic diagram which shows the 6th imaging example of the image for failure diagnosis. The flowchart which shows the 4th example of a failure determination process. The flowchart which shows the 5th example of a failure determination process.

Explanation of symbols

5 Surveillance camera 8 Display unit (LCD: Monitoring information output unit)
A, A ′, A ″, B, B ′, B ″ C ′, C ″ Failure diagnosis image α, β, γ, δ Field of view 22a Security control program (shooting control means for failure diagnosis)
32 Driver's seat DRV driver

Claims (15)

A vehicle security system comprising: a monitoring camera that captures a predetermined monitoring field of view in a vehicle room; and a monitoring information output unit that outputs monitoring information based on an image captured by the monitoring camera,
Fault diagnosis imaging control means for instructing the monitoring camera to capture a fault diagnostic image for the monitoring visual field at two or more predetermined timings;
A failure determination means for comparing the failure diagnosis images captured by the monitoring camera at each timing, and determining a failure of the monitoring camera based on the comparison result;
A failure determination result output means for outputting the failure determination result by the failure determination means;
A vehicle security system characterized by comprising: The failure diagnosis imaging control means provides the failure diagnosis image to the monitoring camera at two timings that are known in advance to cause a difference in image content when the image of the monitoring field of view is normally captured. It is something to shoot,
The vehicle security system according to claim 1, wherein the failure diagnosis unit determines that the monitoring camera has failed when there is no difference between the two photographed failure diagnosis images. One of the two timings is set while the vehicle is parked, and the other is set while the vehicle is running, and the driver's seat of the vehicle is used as the monitoring field of view for capturing the failure diagnosis image. The vehicular security system according to claim 2, wherein a field of view that includes 3. The field of view including a driver's seat of the vehicle is selected as the monitoring field of view for capturing both of the two timings while the vehicle is traveling and taking the failure diagnosis image. Vehicle security system. 5. The vehicle according to claim 3, wherein when the driver is seated in the driver's seat, the field of view including the face is selected as the monitoring field of view for capturing the failure diagnosis image. Security system. Both of the two timings are set while the vehicle is running, and a field of view for photographing the scenery outside the window of the vehicle is selected as the field of view for photographing the failure diagnosis image. Item 3. The vehicle security system according to Item 2. The failure diagnosis imaging control means is configured to detect the failure diagnosis image at two timings in which it is known in advance that there is no difference in image content when the image of the monitoring field of view is normally captured with respect to the monitoring camera. ,
7. The device according to claim 1, wherein the failure diagnosing unit determines that the monitoring camera is broken when there is a difference between the two photographed failure diagnosis images. Vehicle security system. Among the stationary members that are fixedly present inside the running vehicle as the monitoring field for capturing the failure diagnosis image, a predetermined reference member that is in a position that is not obstructed by a passenger of the vehicle The vehicular security system according to claim 2, wherein a field of view in which an image is taken is selected. The vehicle security system according to claim 8, wherein the reference member is a pillar that forms a part of a window frame of the vehicle. The failure diagnosis imaging control means does not match the failure diagnosis image captured at the first timing and the failure diagnosis image captured at the second timing later than the monitoring camera. The failure diagnosis image is additionally photographed at one or more times after the second timing, and the failure determination means is photographed at an adjacent timing after the second timing. The vehicle security system according to any one of claims 7 to 9, wherein normality is determined when the failure diagnosis images match. The vehicle security system according to claim 10, wherein the first timing is set while the vehicle is parked, and the second timing and the additional shooting timing are set while the vehicle is traveling. The failure diagnosis photographing control means provides the first set of the failure diagnosis images to the monitoring camera at two timings in which it is known in advance that the image contents are different in the first monitoring field of view. Two timings that are known in advance that when the image of the monitoring field of view is normally captured in the second monitoring field of view different from the first monitoring field of view, there is no difference in image content. And the second set of the images for failure diagnosis is taken,
The failure diagnosis means determines that the monitoring camera is normal when there is a difference between the first set of failure diagnosis images and when there is no difference between the second set of failure diagnosis images. The vehicle security system according to any one of claims 3 to 11, wherein the vehicle security system is determined. The first monitoring visual field and the second monitoring visual field are set so as to form different parts of the same photographing visual field of the monitoring camera, and the first set of failure diagnosis images and the second monitoring visual field The vehicle security system according to claim 12, wherein a failure diagnosis image at each corresponding timing of a set is simultaneously captured by the monitoring camera. The failure diagnosis shooting control means causes the monitoring camera to take a first failure diagnosis image while the vehicle is parked, and then to take a second failure diagnosis image while the vehicle is running. And the failure diagnosis means compares the first failure diagnosis image with the second failure diagnosis image during the traveling of the vehicle, and determines that a failure has occurred according to the comparison result. The vehicle security system according to any one of claims 1 to 13, wherein a determination output is output to a failure determination result output means provided in the vehicle. The failure diagnosis shooting control means causes the monitoring camera to take a first failure diagnosis image while the vehicle is running, and then to take a second failure diagnosis image while the vehicle is parked. Yes, the failure diagnosis means compares the first failure diagnosis image and the second failure diagnosis image during the parking of the vehicle, and determines that a failure has occurred according to the comparison result. The vehicle security system according to any one of claims 1 to 13, wherein the determination output is wirelessly transmitted to a wireless portable terminal constituting failure determination result output means carried by a user of the vehicle.

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