JP2003242595A - Vehicle detection method and device - Google Patents

Abstract

(57) [Summary] To provide a vehicle detection method capable of improving vehicle detection accuracy. (A) storing vehicle shape template data indicating a feature amount of a contour line indicating at least a part of a shape of a vehicle to be detected; and (b) at least a part of a shape not to be detected. Storing the non-vehicle shape template data indicating the feature amount of the contour line indicating (c), and capturing and binarizing the image of the traveling vehicle to generate a binarized image representing the contour line of the traveling vehicle (E) extracting feature amount data indicating the feature amount of the contour line of the binarized image; and (e).
Comparing each of the vehicle shape template data and the non-vehicle shape template data with the feature amount data, and determining that the detection target is present in the binarized image based on a result of the comparison. Have.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a vehicle detection method and apparatus capable of accurately recognizing a running vehicle and accurately detecting its position.

[0002]

2. Description of the Related Art It is necessary to identify a moving vehicle and identify its position, for example, in order to identify a vehicle that violates the speed limit or a vehicle loaded with dangerous goods whose entry into a long tunnel is prohibited. Is. That is, in order to identify these vehicles, the vehicle number on the license plate of these speeding vehicles and the letters on the plate such as "danger,""poison," and "play" posted on vehicles carrying dangerous goods are used. It is necessary to accurately detect the position that can be accurately read, but in order to do so, first the vehicle itself is accurately detected, and the position of the vehicle on the road is detected, and It is necessary to accurately predict the timing at which the plate that indicates that there is is readable.

In vehicle detection processing by moving image processing to which pattern recognition technology is applied, a large number of vehicle shape patterns (templates) to be detected are registered, and whether or not the vehicle is a vehicle is determined based on the degree of similarity with the registered pattern.

[0004]

In the moving image processing to which the above pattern recognition technique is applied, it is necessary to register a large number of vehicle shape patterns to be detected as templates. For that purpose, a camera is installed on a road or the like. It must be installed and an actual vehicle image must be collected.

Conventionally, as shown in FIG. 7, an actual road 5
A vehicle image capturing camera device 61 and a lighting device 62 are installed at 0 to capture a large number of moving vehicles 2 and a vehicle image recording device 63 records image data. Computer 7 for vehicle shape pattern generation / registration based on the recorded image data
0 generates and registers a vehicle shape pattern (template).

The above method has a problem that it takes time to collect vehicle images. If the number of vehicle images registered as a template is small, sufficient vehicle detection accuracy cannot be obtained. Further, there is a possibility that the registration of the vehicle type may be omitted due to the imbalance of the photographed vehicle type.

An object of the present invention is to provide a vehicle detection method and apparatus which can improve the efficiency of vehicle image collection work and can register a sufficient number of vehicle shapes.

Japanese Patent No. 2893814 discloses that
The following plate cutting device in the vehicle number automatic reading device is disclosed. That is, in a vehicle number automatic reading device for automatically identifying the plate number of a vehicle running or stopped on the road, a photographing means for photographing the road and a plate frame candidate determining means for judging a plate frame candidate from the photographed image. A character area candidate determination means for determining a character area candidate from a captured image; a portion surrounded by a plate frame estimated based on the plate frame candidate; and a character area estimated based on the character area candidate. And a plate position determining means for determining the plate position on the basis of the degree of overlap.

[0009]

According to the vehicle detection method of the present invention, (a) template data indicating a feature amount of a contour line showing at least a part of the shape of a vehicle is generated and stored using computer graphics. Steps,
(B) capturing an image of the traveling vehicle and binarizing the image to generate a binarized image in which the contour of the traveling vehicle is represented; and (c) the feature amount of the contour of the binarized image. Extracting the characteristic amount data shown, and (d) comparing the template data with the characteristic amount data, and determining that a vehicle is included in the binarized image based on the result of the comparison. Is equipped with.

In the vehicle detection method of the present invention, in the step (a), a plurality of template data are generated by changing at least one of an illumination condition and a background for a single vehicle.

In the vehicle detection method of the present invention, (a) generates the template data in consideration of a photographing angle when the traveling vehicle is photographed in (b).

In the vehicle detection method of the present invention, in (a), a three-dimensional model of at least a part of the shape of the vehicle is generated using the computer graphics, and the three-dimensional model of the generated three-dimensional model is generated. The template data indicating the feature amount of the contour line is generated.

In the vehicle detection method of the present invention, the feature amount of the contour line is represented by a vector amount of the direction and size of the contour line.

In the vehicle detection method of the present invention, as the template data, a feature amount of a contour line indicating at least a part of the shape of the vehicle obtained by executing the vehicle detection method at a plurality of locations is stored.

In the vehicle detection method of the present invention, the feature amount data indicates a feature amount of the contour line included in a partial area of the cut out binarized image.

The vehicle detection device of the present invention includes a template data generation / storage section for generating and storing template data indicating the feature amount of the contour line showing at least a part of the shape of the vehicle using computer graphics, and a traveling vehicle. Image capturing unit, and binarize the image to generate a binarized image in which the contour line of the traveling vehicle is represented, and a feature amount indicating a feature amount of the contour line of the binarized image. A feature amount extraction unit that extracts data, the template data, and the feature amount data are compared, and based on the result of the comparison,
The binarized image includes a determination unit that determines that the vehicle is included.

[0017]

BEST MODE FOR CARRYING OUT THE INVENTION An embodiment of a vehicle detection method of the present invention will be described with reference to the accompanying drawings.

FIG. 1 is a schematic block diagram of an apparatus showing this embodiment, FIGS. 2 and 3 are flow charts of a vehicle detection method of this embodiment, and FIG. 4 is a pattern feature amount on a screen imaged by an image pickup apparatus. FIG. 5 is a diagram for explaining a rectangular area used for calculation, and FIG. 5 is an explanatory diagram when a vehicle is detected. Figure 6
FIG. 6 is a diagram for explaining a vehicle shape pattern generation method according to the present embodiment.

In FIG. 1, reference numeral 1 is a road, 2 is a passing vehicle, 3 is a gantry for installing a light source 5 such as a stroboscope for illuminating the vehicle on the road, 4 is an image pickup device for vehicle detection, and 6
Is a position on the road 1 that is optimal for capturing an image of the license plate of the vehicle 2.

Reference numeral 7 is an analog / digital conversion circuit for analog / digital converting the signal from the image pickup device 4, reference numeral 8 is a data smoothing circuit for removing noise,
Reference numeral 9 is an edge enhancement circuit that enhances the edges of the image by subjecting the input image to differential processing using a Sobel differential filter or the like, and reference numeral 10 is a binarization / storage circuit that binarizes and stores the enhanced image.

Further, reference numeral 11 refers to how much and in what direction the contour line of the binarized image has components, that is, how many horizontal components, vertical components and 45 ° components, respectively. , A pattern feature quantity extraction circuit that extracts a pattern feature quantity by expressing it with a vector quantity of the direction and size of the contour line.

Further, reference numeral 12 compares the vehicle shape template of the front shape of the vehicle stored in the vehicle shape template storage device 14 with the pattern feature amount extracted by the pattern feature amount extraction circuit 11 to determine the similarity between the two. This is a comparison / collation circuit for calculating.

Further, reference numeral 13 is a threshold value for checking whether the similarity of the pattern feature amount calculated by the comparison / collation circuit 12 is a certain threshold value or more.

Further, reference numeral 14 expresses the contour direction pattern feature amount in the front shape of the vehicle to be detected by a vector amount of the direction and size of the contour line, stores a certain number of vehicle types as a template, and stores the other types. It is a vehicle shape template storage device that statistically processes and deforms a pattern by a known method to process it so that pattern matching can be performed.

Reference numeral 15 is a database of vehicle CAD data used in CG (computer graphics) technology (see FIG. 6). Reference numeral 80 is
This is a calculation unit (calculator) for vehicle shape pattern generation / registration. The database 15 of vehicle CAD data is, for example,
It can be commercially available. CG application software 81 (see FIG. 6) is installed in the vehicle shape pattern generation / registration calculation unit 80.

Vehicle shape pattern generation / registration computer 80
Uses a computer CAD 81 and vehicle CAD data in the vehicle CAD database 15 to automatically generate a three-dimensional model of the vehicle on a computer. In that case, a model close to the image of the vehicle actually photographed by the image pickup device 4 is automatically generated in consideration of the actual photographing angle and the image pickup range of the image pickup device 4, the color of the light of the light source 5, the light intensity, and the like. Further, the vehicle shape pattern generation / registration computer 80 can prepare a plurality of types of models for one vehicle type by using the CG technology. For example, multiple models can be created by changing the conditions of the light source (whether or not lighting such as a strobe is used, the condition of sunlight, front light, back light, etc.) and the background (weather, time zone, surrounding conditions, etc.). To generate accurate vehicle detection under various conditions.

Vehicle shape pattern generation / registration computer 80
On the basis of the model generated by the CG technique as described above, the vehicle shape pattern serving as template data when performing pattern matching in the comparison / collation circuit 12 described later is automatically generated. The vehicle shape pattern generation / registration computer 80 automatically registers the vehicle shape pattern serving as the template data in the vehicle shape template storage device 14.

Reference numeral 16 indicates that when a vehicle is detected, the vehicle is license plate, "danger", "poison",
A signal is sent to the light source light emission control device 17 that controls the light source 5 such as a strobe to emit light when the optimum timing (position) for reading a plate such as "play" is reached, and the signal is obtained. It is a character recognition control circuit that performs control to receive image pickup data from the binarization / storage device 10.

In the present embodiment, for example, a plurality of image pickup devices 4 and a light source 5 such as a strobe are installed on a gantry 3 provided across the road 1, and the plurality of image pickup devices 4 cover the entire width of the road 1. A vehicle traveling at any position on the road 1 can be captured by capturing an image.

When the vehicle 2 is detected by the vehicle detection device of the present embodiment, the vehicle 2 picks up an image pickup position 6 on the road 1 (the image pickup position 6 in the figure is a temporary frame shown for convenience of explanation. ), The light source 5 such as a strobe is turned on to recognize the characters on the license plate of the vehicle 2 or on the plates such as "danger,""poison," and "drama" posted on vehicles carrying dangerous goods. Recognize the character.

The image pickup device 4 and the light source 5 such as a strobe
Was installed on the gantry 3, but it is obvious that this may be installed on a pillar standing on the roadside.

The image pickup device 4 continuously picks up images of the road 1 to detect the vehicle 2 on the road 1. The detection is performed by the vehicle indicated by the thick line in the imaged image 30 (one frame) shown in FIG. A rectangular area 32 for pattern feature calculation, which is large enough to cover the front surface of the vehicle represented by a plurality of squares in the detection target area 31, is cut out, and the image data therein is stored in the vehicle shape template storage device 14. This is done by comparing with the front pattern template of the vehicle. Image data captured by the image capturing device 4 and the vehicle shape template storage device 1
The pattern matching with the front surface pattern template of No. 4 can be performed by a known method.

The pattern feature quantity calculation rectangular area 32 is cut out in the horizontal (X) direction 33 and the vertical (y) direction within the vehicle detection target area 31.
The vehicle is detected in each of the cut out regions by moving one unit in the direction 34, for example, to the position indicated by (n, m).

Then, this operation is repeated for each frame of the image pickup screen, and when the vehicle 2 is captured at the position of the pattern feature amount calculation rectangular area 32 shown in FIG. 5, vehicle detection is performed at that position. Is determined as.

This determination method will be described with reference to the flow charts shown in FIGS. 2 and 3 and the block diagram of the vehicle detection device of the present embodiment shown in FIG. FIG. 2 and FIG. 3 have a relationship of being connected at the two-dot chain line.

First, in step S21, the pattern feature quantity calculation rectangular area 32 is set to the origin position (n = 0, m = 0) in the vehicle detection target area 31, so that x = 0 and y = 0.

Next, as shown in step S22, one frame 30 of the image pickup screen from the image pickup device 4 is read, analog / digital conversion is performed by the analog / digital conversion circuit 7, and then smoothing is performed as shown in step S23. The noise component is removed by the smoothing circuit 8 by a known smoothing method.

Next, as shown in step S24, the image within the vehicle detection target area 31 of the image pickup screen (one frame) 30 is edge-enhanced by the edge-enhancing circuit 9 using a known Sobel differential filter or the like. Further, as shown in step S25, the edge-enhanced image is binarized by the binarization / storage circuit 10 and stored. The edge emphasizing circuit 9 extracts only the contour of the vehicle by performing two-dimensional differentiation on the image in which the vehicle or the like is shown. The binarization / storage circuit 10 further binarizes the contour of the vehicle.

In the next step S26, the rectangular area 32 for calculating the pattern feature quantity at the origin position of the vehicle detection target area 31 of FIG. 4 in which the vehicle candidate is detected is cut out. next,
In step S27, the pattern feature amount extraction circuit 11 extracts the feature amount of the pattern in the pattern feature amount calculation rectangular area 32. This is to check in which direction and to what extent each of the contour lines of the pattern in which the edges in the pattern feature amount calculation rectangular area 32 are emphasized, that is, to see the vector amount of the direction and size of the contour line. Pattern feature amount is calculated by using, for example, the horizontal component of the contour line,
The magnitudes of the vertical direction component and the 45 ° direction component are calculated to obtain pattern feature amount data.

In step S27, after the pattern feature amount data in the first rectangular region 32 for pattern feature amount calculation is extracted, as shown in step S28,
The collation circuit 12 compares and collates the extracted pattern feature amount data with the vehicle shape template of the front shape of the vehicle stored in the vehicle shape template storage device 14 to calculate and store the degree of similarity. Since this similarity calculation is a value represented by a vector quantity indicating in which direction and in what extent the pattern feature amount data is present as described above, the front surface of the vehicle stored in the vehicle shape template storage device 14 is calculated. It can be easily calculated by comparing with a value indicating the vector amount of the contour line in the vehicle shape template of the shape.
Moreover, since the pattern feature amount data is a value indicating the vector amount of the contour line, the similarity can be calculated regardless of the size of the captured image.

In this way, when the similarity between the pattern feature amount data in the first pattern feature amount calculating rectangular area 32 and the vehicle shape template is calculated and stored, the pattern feature amount of the next pattern feature amount calculating rectangular area 32 is stored. In order to calculate, the pattern feature amount calculation rectangular area 32 is moved by x + in one step in the x direction in step S29.
1 is calculated, and it is determined in step S30 whether the value of x does not exceed the final position coordinate n of the vehicle detection target area 31. In this case, since x is 2, the processing is step S26.
Returning to step S27, the process from step S27 to step S29 described above is repeated, and when the value of x exceeds n in step S30, the process goes to step S31.

Then, in step S31, x is set to 0, and in step S32, y + 1 is calculated in order to move the rectangular region 32 for pattern feature quantity calculation in the y direction by one box, and the value of y is calculated in step S33. It is determined whether the vehicle candidate does not exceed the final position coordinate m of the vehicle detection target area 31 in which the vehicle candidate is detected. In this case, y is 2, so the process returns to step S26, and step S27 described above is executed.
The processing from step S32 is repeated from step S3
When the value of y exceeds m in 3, the process goes to step S34.

Then, in this step S34, the pattern feature amount calculation rectangular area 32 showing the highest similarity between the pattern feature amount data stored in the comparison / collation circuit 12 and the vehicle shape template is selected, and step S34 is selected. This similarity is compared with the threshold 13 in S35.
As a result, when the similarity is higher than the threshold 13, it is determined that the vehicle 2 exists in the pattern feature amount calculation rectangular area 32, a vehicle detection flag is set in step S36, and the vehicle detection result is character recognition control in step S37. It is sent to the circuit 16. When the data for one frame is processed in this manner, the process returns to the first step S21, and the vehicle detection operation described above is repeated.

On the other hand, the character recognition control circuit 16 to which the vehicle detection result is sent receives the pattern feature amount calculation rectangular area in which the vehicle 2 exists in the vehicle detection target area 31 stored in the binarization / storage circuit 10. 32, the size of the vehicle 2 is determined to determine whether it is the optimum timing (position) for reading a license plate or a plate such as “danger,” “poison,” or “play”. If it is determined that the characters are too small in the reading of the plate at this position, the size of the vehicle 2 and the position where the vehicle 2 is detected in the next frame or in the next frame, and the size of the vehicle 2 in the previous frame. The speed of the vehicle 2 is calculated according to the change from the position or size of the vehicle 2, and the license plate or "danger",
The optimum timing (position) for reading a plate such as "poison" or "drama" is calculated, and a signal is sent to the light source emission control circuit 17.

Therefore, the light source light emission control device 17 is provided in the vehicle 2
The light source 5 such as a strobe light is emitted at the optimum timing (position) to read the license plate of "No", "dangerous", "poison", "drama", etc. Smoothing circuit 8 through 7
After being smoothed by, the character plate is sent to the character recognition control circuit 16 and the character recognition circuit (not shown) recognizes the license plate of the vehicle 2 and characters such as “danger”, “poison”, and “play”.

As described above, the vehicle shape template storage device 14 registers the vehicle template automatically created on the vehicle shape pattern generation / registration computer 80 using the vehicle CAD data. Conventionally, the work efficiency is higher than that in which a vehicle template can be created only by installing a camera on a road or the like and collecting actual vehicle images in advance.

In addition, in the vehicle shape pattern registration by actual vehicle image collection, registration omission may occur, but in the present embodiment, an assumed vehicle image can be created without leaking by CG technology, so vehicle detection is performed. Leads to improved accuracy.

In the above embodiment, before the vehicle detection device of this embodiment is installed, the vehicle shape template generated by the vehicle shape pattern generation / registration computer 80 by the CG technology using the vehicle CAD data is the vehicle shape template storage device. 14 is stored. After the installation of the vehicle detection device of the present embodiment, the shape pattern of the actual vehicle captured by the imaging device 4 is automatically registered in the vehicle shape template storage device 14 in addition to the CG vehicle shape pattern before installation of the device. be able to. In that case, the shape pattern of the actual vehicle photographed by the imaging device 4 is converted into the vehicle shape pattern of CG, and then the vehicle shape template storage device 1 is used.
4 can be registered.

Further, the vehicle detection device of the present embodiment is installed at a large number of points, the devices installed at the large number of points are mutually connected by a network, and the vehicle shape patterns obtained by the respective devices are mutually connected. The detection accuracy is improved by automatically registering in each device by reflecting the above. In this case, the vehicle shape pattern obtained by each device,
Are collectively processed and managed by the host computer, and the host computer can transmit the data to each device.

Further, according to this embodiment, the vehicle 2 can be operated by the single image pickup device 4 without separately providing a vehicle position detecting device using a laser, an ultrasonic wave, a loop coil or the like.
Timing (position) for recognizing information, reading license plates and plates such as "danger,""poison," and "play"
And calculation of image data for recognizing these characters can be performed. Moreover, the recognition of the vehicle is
By using the contour direction pattern feature amount, it can be performed even if the vehicle is far away, and the shadow of the vehicle itself and the shadow of the building are not mistaken for the vehicle, and the license plate of the vehicle and the " A vehicle detection method and device optimal for recognizing characters such as "danger", "poison", and "play" can be provided.

In the above description, the analog / digital conversion circuit 7, the smoothing circuit 8, the edge emphasizing circuit 9, the binarization / storage circuit 10, for processing the signal from the image pickup device 4,
Pattern feature quantity extraction circuit 11, comparison / collation circuit 12, threshold value 13, vehicle shape template storage device 14, vehicle CA
D data database 15, character recognition control circuit 16,
It has been described that the light source emission control device 17, the vehicle shape pattern generation / registration calculation unit 80, and the like are used.
It goes without saying that circuits other than the digital conversion circuit 7 may be configured using a computer and its storage device.

[0052]

According to the vehicle detection method of the present invention, vehicle detection accuracy is improved.

[Brief description of drawings]

FIG. 1 is a schematic block diagram of an apparatus showing an embodiment of a vehicle detection method of the present invention.

FIG. 2 is a flowchart showing a part of the vehicle detection method of the present embodiment.

FIG. 3 is a flowchart of another part of the vehicle detection method of the present embodiment.

FIG. 4 is a diagram for explaining a rectangular area used for pattern feature amount calculation on a screen imaged by an imaging device in the present embodiment.

FIG. 5 is an explanatory diagram when a vehicle is detected in the present embodiment.

FIG. 6 is a diagram for explaining a vehicle shape pattern generation method according to the present embodiment.

FIG. 7 is a diagram for explaining a conventional vehicle shape pattern generation method.

[Explanation of symbols]

1 road 2 passing vehicles 3 gantry 4 Vehicle detection imaging device 5 light sources 6 Imaging position on the road 7 Analog / digital conversion circuit 8 Smoothing circuit 9 Edge enhancement circuit 10 Binarization / memory circuit 11 Pattern feature extraction circuit 12 Comparison / collation circuit 13 threshold 14 Vehicle shape template storage device 15 Vehicle CAD data database 16 character recognition control circuit 17 Light source emission control device Fifty roads 61 Vehicle image capturing camera device 62 Lighting device 63 Vehicle image recording device 80 Vehicle shape pattern generation / registration calculation unit (calculator)

─────────────────────────────────────────────────── ─── Continuation of front page (51) Int.Cl. ⁷ Identification code FI theme code (reference) H04N 7/18 H04N 7/18 K (72) Inventor Atsushi Kuroda 2-1-1 Niihama, Arai-cho, Takasago-shi, Hyogo Prefecture No. Mitsubishi Heavy Industries, Ltd. Takasago Research Institute (72) Inventor Katsushi Ikeuchi 2F, 2F, Umegaoka, Aoba-ku, Yokohama, Kanagawa 5B050 BA09 EA06 EA18 EA28 FA02 5B057 AA16 BA29 CA08 CB06 CB13 CE12 CH01 CH11 DA06 DC01 DC16 5C054 AA01 CE15 CH01 EA01 ED07 EJ04 FC05 HA30 5H180 AA01 BB05 CC04 DD10 EE02 EE07 5L096 BA04 CA02 FA06 JA09 JA11 KA13

Claims (8)

[Claims] 1. A step of (a) generating and storing template data indicating a feature amount of a contour line showing at least a part of a shape of a vehicle by using computer graphics, and (b) capturing an image of a traveling vehicle. And binarizing to generate a binarized image in which the contour line of the traveling vehicle is represented, and (c) extracting feature amount data indicating the feature amount of the contour line of the binarized image. , (D) comparing the template data with the feature amount data,
A vehicle detection method comprising: determining that a vehicle is included in the binarized image based on a result of the comparison. 2. The vehicle detection method according to claim 1, wherein (a) changes at least one of an illumination condition and a background of a single vehicle to generate a plurality of template data. Method. 3. The vehicle detection method according to claim 1, wherein the (a) includes the template data in consideration of a photographing angle when the traveling vehicle is photographed in the (b). Vehicle detection method to generate. 4. The vehicle detection method according to claim 1, wherein the (a) uses the computer graphics to generate a three-dimensional model of at least a part of the shape of the vehicle. A vehicle detection method for generating and generating the template data indicating the feature amount of the contour line of the generated three-dimensional model. 5. The vehicle detection method according to claim 1, wherein the feature amount of the contour line is represented by a vector amount of the direction and size of the contour line. 6. The vehicle detection method according to claim 1, wherein the template data is at least a part of a vehicle shape obtained by executing the vehicle detection method at a plurality of locations. The vehicle detection method in which the feature amount of the contour line indicating the is stored. 7. The vehicle detection method according to claim 1, wherein the feature amount data is a feature of the contour line included in a partial region of the cut out binarized image. Vehicle detection method that indicates quantity. 8. A template data indicating a feature amount of a contour line showing at least a part of a shape of a vehicle is stored in a computer.
A template data generation storage unit that generates and stores using graphics, and a binarized image generation unit that captures an image of a traveling vehicle and binarizes it to generate a binarized image in which the contour line of the traveling vehicle is represented. And a feature quantity extraction unit that extracts feature quantity data indicating the feature quantity of the contour line of the binarized image, the template data and the feature quantity data are compared, and based on a result of the comparison, A vehicle detection device comprising: a determination unit that determines that the binary image includes a vehicle.