JP5304064B2 - Speed measuring device and speed measuring method - Google Patents

Description

  The present invention relates to a speed measuring device and a speed measuring method for measuring a speed based on captured image information.

There is a known speed measurement device that obtains the amount of rotation of a tire and calculates the speed based on the travel distance calculated from the amount of rotation. there were.
Therefore, a speed measuring device is known that calculates the speed by capturing the ground with a camera such as a CCD, detecting edges from the captured image, obtaining the number of moving pixels for a plurality of edges, and calculating the average value thereof. (See Patent Document 1).

JP 2006-221461 A

  However, since the conventional technique calculates the speed by averaging the number of moving pixels of the edge, when the moving body suddenly starts (rapidly moves), the edge shift immediately after the start of movement becomes large. For this reason, there is a case where the error of the moving speed becomes large only by calculating the speed by averaging the number of moving pixels of the edge, and there is a problem that the calculation accuracy of the moving speed is lowered.

  The problem to be solved by the present invention is to appropriately measure the speed based on the captured image information.

According to the present invention, for each piece of image information , based on the size of the plurality of imaging ranges corresponding to each of the plurality of pixels and the position on the imaging device of the pixel on which the image information was imaged before and after a predetermined time elapsed. The maximum movement distance L1 and the minimum movement distance L2 of the image information are calculated, and for each of the plurality of image information, the maximum movement speed V1 is calculated from the maximum movement distance L1, and the minimum movement speed V2 is calculated from the minimum movement distance L2. A minimum value V1 _{min of} the plurality of maximum movement speeds V1 calculated from the image information and a maximum value V2 _{max of} the plurality of minimum movement speeds V2 are calculated, and the calculated minimum value V1 _min and maximum value V2 _max are calculated. Since the speed information is calculated based on the movement speed, even when the mobile body starts suddenly (moves rapidly), the edge deviation immediately after the start of movement can be reduced. The calculation accuracy of can be improved.

  According to the present invention, the speed information is calculated using the moving distance calculated based on the imaging range of each pixel and the position information in the pixel array of the image information. Even in the case of rapid movement), the shift of the edge immediately after the start of movement can be reduced, so that the calculation accuracy of the movement speed can be increased.

  The speed measurement device according to the present embodiment is a device that is mounted on a moving body such as a vehicle and measures the speed on the basis of captured images around the moving body.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

  FIG. 1 is a block diagram of a speed measuring device 1 according to this embodiment. As shown in FIG. 1, the speed measurement device 1 of the present embodiment includes an imaging device 2 that captures an image, and a control unit CU that calculates speed information from the captured image information.

  Each configuration will be described below.

  The imaging device 2 has a plurality of pixels on the imaging device and captures a luminance image. Examples of the imaging device include a charge coupled device (CCD) and a complementary metal oxide semiconductor (CMOS).

  FIG. 2 is a schematic diagram illustrating a relationship between the installation state of the imaging device 2 and the imaging target region 4. In FIG. 2, the moving body on which the imaging device 2 is mounted travels in the X-axis direction, and FIG. 2 is a diagram of the imaging device 2 viewed from the Y-axis direction. In the present embodiment, the imaging device 2 is installed on the moving body so as to have a height H with respect to the imaging target. As an imaging target, for example, when the moving body in the present embodiment is an automobile, it can be the ground. The imaging device 2 images the imaging target area 4. The imaging target area 4 captured by the imaging device 2 is not particularly limited. In the present embodiment, as shown in the figure, the imaging device 2 is tilted forward by an angle α in the traveling direction of the moving body, thereby moving forward in the traveling direction. The lower fixed area is imaged.

  The imaging device 2 images the imaging target region 4 at a predetermined cycle (frame rate). Then, the imaging device 2 inputs the captured imaging information to the control unit CU.

  The control unit CU calculates the speed based on the imaging information captured by the imaging device 2. The control unit CU of the present embodiment includes a ROM (Read Only Memory) in which a program or firmware is stored, a CPU (Central Processing Unit) that functions as the control unit CU by executing the program stored in the ROM, RAM (Random Access Memory) as a storage unit.

  As shown in FIG. 1, the control unit CU of the present embodiment includes an edge extraction unit 31, a position information detection unit 32, an imaging range calculation unit 33, a movement distance calculation unit 34, and a speed information calculation unit 35.

  The internal configuration of the control unit CU will be described.

  First, the edge extraction unit 31 will be described. The edge extraction unit 31 extracts the edge (contour) of the imaging target from the imaging information input from the imaging device 2.

  The edge extraction method is not particularly limited. For example, a method of extracting an edge using a filter such as a Sobel filter or a Prewitt filter, which is a primary difference filter, a horizontal or vertical primary spatial differential filter, a secondary spatial differential filter, a nonlinear differential filter, or the like. .

Next, the position information detection unit 32 will be described. The position information detection unit 32 detects the position in the pixel array of the pixel from which each edge is extracted.
FIG. 3 is a schematic diagram showing the relationship between the position in the pixel array of each pixel and the pixel number in the present embodiment. As shown in FIG. 3, for example, the number on the front left side is (0, 0), and numbers are assigned to each pixel so that the numbers increase in the X-axis and Y-axis directions. For example, the pixel at the p-th position in the X-axis direction and the q-th position in the Y-axis direction has a pixel number (p, q). Thus, by assigning a number to each pixel on the image sensor, it is possible to grasp the position in the pixel array of the pixel from which each edge is extracted.

Next, the imaging range calculation unit 33 will be described. The imaging range calculation unit 33 calculates an imaging range that can be captured for each pixel on the imaging element. The imaging range refers to an area that can be imaged with one pixel in the imaging target area 4.
4 and 5 are schematic diagrams illustrating the relationship between the imaging angle and the imaging range of each pixel of the imaging device 2 in the present embodiment. 4 is a perspective view of the imaging device 2 and the imaging target region 4 from the Y-axis direction, while FIG. 5 is a diagram of the imaging device 2 and the imaging target region 4 viewed from above. 4 and 5, a set of imaging ranges captured by pixels arranged in 6 columns × 5 columns that capture an area far from the imaging device 2 is referred to as an imaging region A. A set of imaging ranges captured by pixels arranged in 6 vertical columns × 5 horizontal rows that capture a close region is referred to as an imaging region B.

As shown in FIG. 4, the imaging angle of the pixel that captures the imaging area A that is far (front) from the imaging device 2 is relatively small with respect to the imaging area A. As a result, the imaging range in which the pixels for imaging the imaging area A can be imaged with one pixel is widened. On the other hand, the imaging angle with respect to the imaging region B of the pixel that images the imaging region B near (near) the imaging device 2 is close to a right angle. As a result, the imaging range in which the pixel that captures the imaging region B can be captured by one pixel is narrowed. That is, as shown in FIG. 5, the imaging range becomes wider as the pixel that captures the farther imaging target region 4, while the imaging range becomes narrower as the pixel that captures the nearby imaging target region 4.
In FIGS. 4 and 5, as an example, only the imaging area A and the imaging area B that are part of the imaging target area 4 have been described, but in reality, imaging is performed using all pixels and the pixels. In relation to the imaging range to be performed, the imaging range becomes wider as the pixel that captures the farther imaging target region 4, while the imaging range becomes narrower as the pixel that captures the nearby imaging target region 4.

As described above, the imaging range is different for each pixel. Therefore, a method for calculating an imaging range that can actually be captured by each pixel will be described below. In the present embodiment, the imaging range of each pixel is calculated based on imaging conditions such as the height from the imaging device to the imaging target, the tilt angle of the imaging device with respect to the imaging target, the resolution of the imaging device, and the angle of view. FIG. 6 is a view of the imaging device 2 and the imaging target region 4 in this embodiment as viewed from above. As shown in FIGS. 2 and 6, in the present embodiment, the height from the imaging device 2 to the imaging target is H, and the angle from the imaging device 2 to the imaging target is α. Further, the resolutions of the imaging device 2 in the X-axis and Y-axis directions are a and b, respectively, and the field angles of the imaging device 2 in the X-axis and Y-axis directions are φ _x and φ _y , respectively. Here, when the imaging target region 4 is assumed to be a plane, the specific imaging range of the pixel at the position of the pixel number (p, q), that is, the length Lx in the X-axis direction of the imaging range and the imaging range Y The axial length Ly can be calculated from, for example, the following formulas (1) and (2).

  Note that the imaging range calculation method is not limited to the above-described method. For example, a distance measuring device may be used to calculate the distance for each pixel, and the imaging range may be calculated therefrom.

Next, the movement distance calculation unit 34 will be described. The movement distance calculation unit 34 calculates the difference in position on the pixel array of the pixels from which the respective edges are extracted before and after the elapse of a predetermined time as the number of moving pixels of the edge.
FIG. 7A is a diagram illustrating an example of a scene of an imaging range of a pixel from which an edge is extracted and its surrounding pixels at the time of N frame imaging. FIG. 7B is a diagram showing an example of a scene of an imaging range of a pixel from which an edge is extracted and its surrounding pixels after a lapse of one frame time from FIG. 7A. FIG. 7A shows a case where an edge is extracted by pixels that image the imaging range C by the edge extraction unit 31 during imaging of N frames. FIG. 7B shows a case where the same edge is extracted by pixels that capture the imaging range C ′ when the edge extraction unit 31 captures N + 1 frames after the time of one frame has elapsed. From FIG. 7A and FIG. 7B, the edge extracted by the pixel that captures the imaging range C has moved a distance of 4 pixels to the pixel that captures the imaging range C ′ after one frame time has elapsed. That is, the number of moving pixels of the edge extracted by the pixels that capture the imaging ranges C and C ′ is 4.
In the present embodiment, the edges extracted by the pixels that capture the imaging ranges C and C ′ by obtaining the optical flow from the imaging information at the N frame and the imaging information at the N + 1 frame are the same imaging object. It can be determined that this is an edge extracted from.

  Here, the method for calculating the number of moving pixels of the edge is not particularly limited. In this embodiment, the number of moving pixels of the edge is calculated using an optical flow, but the optical flow method is not limited. For example, a correlation method that uses block matching such as template matching between frames to determine corresponding points and obtains a motion vector, or a gradient method that uses the relationship between the spatial and temporal gradients of the brightness of each point The method of using is mentioned.

Subsequently, the moving distance calculating unit 34 determines the maximum moving distance L1 and the minimum moving distance of each edge based on the imaging range of each pixel from which the edge is extracted by the edge extracting unit 31 and the number of moving pixels of each edge. L2 is calculated.
7C shows the maximum movement distance L1 and the minimum movement distance L2 when the edge extracted in the pixel that captures the imaging range C shown in FIG. 7A moves to the position of the pixel that captures the imaging range C ′ shown in FIG. 7B. FIG. In the present embodiment, the maximum moving distance L1 and the minimum moving distance L2 of each edge are distances that take into consideration the size of the imaging ranges in each pixel, that is, the imaging ranges C and C ′, and the maximum moving distance L1. Is the maximum distance from the imaging range C to the imaging range C ′, and the minimum moving distance L2 is the minimum distance from the imaging range C to the imaging range C ′. Therefore, the maximum movement distance L1 is longer than the minimum movement distance L2 by a distance corresponding to the imaging range C + C ′.

  FIG. 8A is a diagram illustrating another scene example of an imaging range of a pixel from which an edge is extracted and its surrounding pixels at the time of N frame imaging. 8B is a diagram illustrating another scene example of the imaging range of the pixel from which the edge is extracted and its surrounding pixels after one frame time has elapsed since the imaging in FIG. 8A. FIG. 8A shows a case where an edge is extracted from the pixels that capture the imaging range D and the pixels that capture the imaging range E by the edge extraction unit 31 during N frame imaging. FIG. 8B shows a case where an edge is extracted by pixels that capture the imaging range D ′ and the imaging range E ′ by the edge extraction unit 31 at the time of N + 1 frame imaging after one frame time has elapsed. 8A and 8B, when the time for one frame has elapsed, the edge extracted by the pixel that captures the imaging range D moves to the position of the pixel that captures the imaging range D ′. The edge extracted by the pixel to be imaged has moved to the position of the pixel to be imaged in the imaging range E ′.

8C to 8E are diagrams for explaining the maximum movement distance L1 and the minimum movement distance L2 of both edges extracted in FIGS. 8A and 8B. Here, the distance d shown in FIG. 8C is the distance that both edges have actually moved. Since the distance d is the distance that both edges have actually moved, the distance d is equal for both edges. That is, the edges extracted from the pixels that capture the imaging range D are from the imaging range D to the imaging range D ′, and the edges extracted from the pixels that capture the imaging range E are from the imaging range E to the imaging range E ′. The same distance d is moved. However, the imaging range D that is a region far from the imaging device 2 has a wide imaging range, and the imaging range E that is a region near the imaging device 2 has a narrow imaging range. Therefore, as shown in FIG. 8C, the edge extracted in the imaging range D and the edge extracted in the imaging range E are actually moved the same distance d, but the imaging range is wide. The number of moving pixels of the edge between the ranges DD ′ is 2 pixels, and the number of moving pixels of the edges between the imaging ranges EE ′ having a narrow imaging range is 3 pixels.
FIG. 8D is a diagram showing the maximum edge movement distance L1 (D) extracted in the imaging range D and the maximum edge movement distance L1 (E) extracted in the imaging range E. Although both edges actually move the same distance d, but the imaging ranges are different, the maximum edge movement distance L1 (D) extracted in the imaging range D is the maximum edge movement distance extracted in the imaging range E. It can be seen that it is longer than L1 (E).
8E is a diagram showing the minimum edge movement distance L2 (D) extracted in the imaging range D and the minimum edge movement distance L2 (E) extracted in the imaging range E. Although both edges actually move the same distance d, but the imaging range is different, the minimum moving distance L2 (D) of the edge extracted in the imaging range D is the minimum moving distance of the edge extracted in the imaging range E. It can be seen that it is shorter than L2 (E).

Thus, even when each edge actually moves the distance d which is the same moving distance, the number of moving pixels of each edge, the maximum moving distance L1 and the minimum moving distance L2 are different because the imaging range for each pixel is different. Different. That is, since the imaging range is different for each pixel, a plurality of different maximum movement distances L1 and minimum movement distances L2 can be calculated from a plurality of edges.
Note that each edge exists on the imaging range captured by the pixel from which each edge is extracted. Therefore, the actual movement distance of each edge does not become larger than the maximum movement distance L1, and is minimum. It does not become smaller than the movement distance L2.

Next, the speed information calculation unit 35 will be described. The speed information calculation unit 35 calculates the speed of the moving object from the distance information calculated by the movement distance calculation unit 34.
First, the speed information calculation unit 35 calculates a maximum movement speed V1 and a minimum movement speed V2 corresponding to the maximum movement distance L1 and the minimum movement distance L2 for each edge calculated by the movement distance calculation unit 34. Here, assuming that the imaging time of one frame is t, the maximum moving speed V1 and the minimum moving speed V2 are obtained by the following equation (3).

本実施形態において、撮像装置２により撮像された撮像情報において抽出されたエッジの数をｅとすると、速度情報算出部３５では、複数のエッジ１〜ｅについての最大移動速度Ｖ１（１）、Ｖ１（２）、・・・、Ｖ１（ｅ）と最小移動速度Ｖ２（１）、Ｖ２（２）、・・・、Ｖ２（ｅ）とを算出することとなる。

In the present embodiment, when the number of edges extracted in the imaging information captured by the imaging device 2 is e, the speed information calculation unit 35 uses the maximum movement speeds V1 (1) and V1 for the plurality of edges 1 to e. (2),..., V1 (e) and minimum moving speeds V2 (1), V2 (2),..., V2 (e) are calculated.

Then, the speed information calculation unit 35 calculates the minimum value V1 _min among the maximum movement speeds V1 (1), V1 (2)..., V1 (e) calculated for the plurality of edges and the plurality of edges. The maximum value V2 _max among the calculated minimum moving speeds V2 (1), V2 (2)..., V2 (e) is calculated by the following equations (4) and (5).

FIG. 9 is a diagram showing a speed range obtained from the maximum movement speed V1 and the minimum movement speed V2 of each edge. FIG. 9 shows an example of the minimum movement speeds V1 (1) to V1 (e) and the maximum movement speeds V2 (1) to V2 (e) of the edges 1 to e extracted in the present embodiment. In the example shown in FIG. 9, the minimum value V1 _min in the maximum movement speed V1 of each edge becomes the maximum movement speed V1 (2) of the edge 2, and the maximum value V2 _{max in} the minimum movement speed V2 of each edge. Becomes the minimum moving speed V2 (4) of the edge 4, and the actual speed of the moving object is between V1 (2) having the minimum value V1 _min and V2 (4) having the maximum value V2 _max. .

Therefore, in the present embodiment, the speed information calculation unit 35 determines the final moving speed V of the moving body from the minimum value V1 _min of the maximum moving speed and the maximum value V2 _max of the minimum moving speed in the following equation (6). calculate.

In this way, the maximum movement speed V1 and the minimum movement speed V2 are calculated from the maximum movement distance L1 and the minimum movement distance L2 for a plurality of edges, respectively, and the closest to the actual speed is calculated from the maximum movement speed V1 and the minimum movement speed V2. By calculating the speed of the minimum value V1 _{min at the} maximum movement speed V1 and the maximum value V2 _{max at} the minimum movement speed V2, the speed can be measured more appropriately.
In the present embodiment, more edges can be detected by tilting the imaging device 2 to the lower front, and as a result, more maximum movement speed V1 and minimum movement speed V2 can be calculated. . Furthermore, since the imaging range is different for each pixel, more maximum moving speed V1 and minimum moving speed V2 can be calculated. In this way, the maximum moving speed V1 and the minimum moving speed V2 are calculated, and the minimum value V1 _min and the maximum value V2 _max are calculated using the maximum moving speed V1 and the minimum moving speed V2. The speed range can be narrowed down, and the speed can be measured more appropriately.

  Next, the operation procedure of the speed measuring device 1 of the present embodiment will be described based on the flowchart of FIG.

  The imaging device 2 captures an image of the imaging target area 4 at a predetermined cycle (frame rate), and inputs the imaging information to the control unit CU (step S1). The edge extraction unit 31 extracts the edge (contour) of the imaging target from the imaging information (step S2). The position information detection unit 32 detects the position in the pixel array of the pixel from which each edge is extracted (step S3).

The imaging range calculation unit 33 includes a height H from the imaging device 2 to an imaging target, an inclination angle α with respect to the imaging target of the imaging device 2, resolutions a and b of the imaging device 2, and an angle of view φ _x and φ of the imaging device 2. Based on _y , the imaging range of each pixel is calculated from the imaging information captured by the imaging device 2 (step S4).

The movement distance calculation unit 34 calculates the difference in position in the pixel array of the pixels from which the edges before and after the elapse of the predetermined time are extracted as the number of edge movement pixels. Further, the maximum movement distance L1 and the minimum movement distance L2 of each edge are calculated based on the calculated number of moving pixels of each edge and the imaging range of each pixel calculated by the imaging range calculation unit 33 (step S5). . The speed information calculation unit 35 obtains the maximum movement speed V1 and the minimum movement speed V2 from the maximum movement distance L1 and the minimum movement distance L2 of each edge calculated by the movement distance calculation unit 34, and is obtained from a plurality of edges. The minimum value V1 _min for the maximum moving speed V1 and the maximum value V2 _max for the minimum moving speed V2 obtained from a plurality of edges are calculated to calculate the final moving body speed V (step S6). .
Step S4 may be performed before step S2, and step S2, step S3, and step S4 may be performed simultaneously.

  The speed measurement device 1 of the present embodiment is configured and operates as described above, and therefore has the following effects.

  The speed measurement device 1 according to the present embodiment calculates an imaging range for each pixel from which an edge is extracted, and moves based on the calculated imaging range and position information in the pixel array of the pixel from which each edge is extracted. Since the distance is calculated, the speed can be measured appropriately.

In particular, in the present embodiment, taking into consideration that the imaging range is different for each pixel, a plurality of different maximum movement speeds V1 and minimum movement speeds V2 are calculated for a plurality of edges. Then, the minimum value V1 _min is calculated from the maximum movement speed V1 calculated for the plurality of edges, and the maximum value V2 _max is calculated from the minimum movement speed V2 calculated for the plurality of edges, and these minimum values V1 _min are calculated. The final speed is calculated based on the maximum value V2 _max . In other words, in this embodiment, the speed V1 _min and the maximum value V2 _max are calculated from a plurality of different speeds calculated from a plurality of edges, and the final speed is calculated from these speeds. The speed can be measured more appropriately without being determined by the resolution (number of pixels) of the imaging device 2.

Furthermore, in this embodiment, since the imaging device 2 is tilted forward in the traveling direction of the moving body, the pixels of the farther imaging target region 4 are imaged with respect to the imaging range captured by the imaging device 2. The imaging angle becomes smaller and the imaging range becomes wider. On the other hand, the closer the pixel that captures the imaging region 4 is, the closer the imaging angle of the imaging device 2 to the imaging range captured by the imaging device 2 is, and the imaging range becomes narrower. In this way, since the speed is calculated based on the different imaging range for each pixel, a plurality of different pieces of speed information can be acquired for each edge as compared to the case where the imaging range is regarded as constant and the speed is calculated. . As a result, the speed range between the minimum value V1 _min and the maximum value V2 _max can be narrowed, so that the speed can be measured more appropriately.

In addition, in the present embodiment, by imaging with the imaging device 2 tilted forward, the imaging target region 4 itself becomes extensive, and the amount of edges to be imaged increases. Therefore, more speed information can be acquired. As a result, as described above, the speed range between the minimum value V1 _min and the maximum value V2 _max can be narrowed, so that the speed can be measured more appropriately.

  In addition, since the imaging device 2 can be tilted forward and imaged, it can be mounted on a vehicle compared to the case where the imaging device is installed directly below the ground as in the prior art. Is preferred. In addition, it can be expected that the imaging device 2 is also used for purposes other than speed measurement. For example, by combining with the use of distance measurement, it is possible to measure not only the speed measurement but also the behavior (pitch, yaw) of the apparatus.

  The embodiment described above is described for facilitating the understanding of the present invention, and is not described for limiting the present invention. Therefore, each element disclosed in the above embodiment is intended to include all design changes and equivalents belonging to the technical scope of the present invention.

  That is, in the present embodiment, the present invention is described as an example of mounting the present invention on a vehicle as a speed measuring device, but the present invention is not limited to this. For example, railways, ships, other mobile objects, industrial robots, and security robots. It can also be applied to devices that control the operation of nursing robots and other robots, industrial equipment, etc., and equipment that measures the position of a stationary object or a moving object.

It is a block diagram of speed measuring device 1 of this embodiment. It is a schematic diagram which shows the relationship between the installation state of the imaging device 2 of this embodiment, and the imaging target area | region 4. FIG. It is a schematic diagram which shows the relationship between the position in the pixel arrangement | sequence of each pixel in this embodiment, and a pixel number. FIG. 2 is a schematic diagram illustrating a relationship between an imaging angle of each pixel and an imaging range of the imaging device 2 according to the present embodiment, and a perspective view of the imaging range 2. FIG. 4 is a schematic diagram illustrating a relationship between an imaging angle of each pixel and an imaging range of the imaging device 2 in the present embodiment, and is a diagram of the imaging range 2 as viewed from above. It is the figure which looked at the imaging device 2 and the imaging object area | region 4 in this embodiment from the top. It is a figure which shows the example of 1 scene of the imaging range of the pixel from which the edge at the time of N frame imaging was extracted, and its surrounding pixel. It is a figure which shows the example of 1 scene of the imaging range of the pixel from which the edge at the time of N + 1 frame imaging was extracted, and its surrounding pixel. It is a figure for demonstrating the maximum moving distance L1 and the minimum moving distance L2 of the edge of FIG. 7A and FIG. 7B. It is a figure which shows the other example of a scene of the imaging range of the pixel from which the edge at the time of N frame imaging was extracted, and its surrounding pixel. It is a figure which shows the other example of a scene of the imaging range of the pixel from which the edge at the time of N + 1 frame imaging was extracted, and its surrounding pixel. It is a figure for demonstrating the number of moving pixels of the edge of FIG. 8A and FIG. 8B, and the moving distance d of an actual edge. It is a figure for demonstrating the maximum moving distance L1 of the edge of FIG. 8A and FIG. 8B. It is a figure for demonstrating the minimum moving distance L2 of the edge of FIG. 8A and FIG. 8B. It is a figure which shows the speed range calculated | required from the maximum moving speed V1 and the minimum moving speed V2 of each edge. It is a flowchart which shows the flow of a process in the speed measurement apparatus 1 of this embodiment.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Speed detection apparatus 2 ... Imaging device CU ... Control unit 31 ... Edge extraction part 32 ... Position information detection part 33 ... Imaging range calculation part 34 ... Movement distance calculation part 35 ... Speed information calculation part 4 ... Imaging object area | region

Claims (6)

An imaging means having an imaging device comprising a plurality of pixels;
A position information detecting means in which a plurality of image information captured to detect image information position is the position on the imaging element of the pixel captured by the imaging device,
It is a range that is imaged by the pixels and has a size according to the distance from the imaging means in the traveling direction.
An imaging range calculation means for calculating a different range as the imaging range for each pixel ,
And sizes of a plurality of the imaging range corresponding to the plurality of pixels, and based on the said image information position before and after the course has been predetermined time detected by the position information detecting means, for each of the image information, the image A moving distance calculating means for calculating a maximum moving distance L1 and a minimum moving distance L2 of information ;
For each of the plurality of image information, the maximum movement speed V1 is calculated from the maximum movement distance L1, the minimum movement speed V2 is calculated from the minimum movement distance L2, and the plurality of maximum movement speeds calculated from the plurality of image information. A minimum value V1 _min of V1 and a maximum value V2 _{max of} the plurality of minimum moving speeds V2 are calculated , and speed information is calculated based on the calculated minimum value V1 _min and maximum value V2 _max. And a speed information calculating unit. The speed measuring device according to claim 1,
The speed measurement apparatus according to claim 1, wherein the image information is information processed by an edge extraction unit that extracts an edge from an image captured by the image sensor . In the speed measuring device according to claim 1 or 2,
The speed measuring apparatus according to claim 1, wherein the imaging unit images a lower front portion in a moving direction as a target area. In the speed measuring device according to any one of claims 1 to 3 ,
The speed measurement apparatus according to claim 1, wherein the imaging range calculation unit calculates an imaging range of a plurality of pixels based on an imaging condition of the imaging unit. The speed measuring device according to claim 4 ,
Imaging condition in the imaging range calculating means, and wherein the height with respect to the imaging target of the imaging means, at least one condition of the angle of view angle, the resolution of the imaging unit, and the imaging means for imaging target Speed measuring device. It captures an image by an imaging device having a plurality of pixels,
A range that is imaged by the pixel and that varies in size according to the distance from the imaging element in the traveling direction is calculated for each pixel as an imaging range,
And sizes of a plurality of the imaging range corresponding to the plurality of pixels, before and after a predetermined time, the image information on the basis of the position on the image sensor pixel imaged, for each of the image information, the image information The maximum movement distance L1 and the minimum movement distance L2 are calculated, and for each of the plurality of pieces of image information, the maximum movement speed V1 is calculated from the maximum movement distance L1, and the minimum movement speed V2 is calculated from the minimum movement distance L2. And calculating a minimum value V1 _min of the plurality of maximum movement speeds V1 calculated from the image information and a maximum value V2 _{max of} the plurality of minimum movement speeds V2, and calculating the minimum value V1 _min and A speed measurement method for calculating speed information based on the maximum value V2 _max .

Images