JP3503840B2 - Vehicle periphery monitoring device - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a vehicle periphery monitoring device which is effectively applied to monitor the periphery of a vehicle such as an automobile and assist the driver's safety confirmation in driving the vehicle.
More specifically, the present invention relates to a vehicle periphery monitoring device that recognizes an object such as an obstacle based on image information captured by two cameras (imaging means) installed in a vehicle.

[0002]

2. Description of the Related Art Conventionally, as a vehicle periphery monitoring device of this type, for example, Japanese Patent Laid-Open No. 4-261000 and Japanese Patent Laid-Open No. 4-261000.
There is a device disclosed in Japanese Patent Laid-Open No. 301513 (hereinafter, these are collectively referred to as a conventional device). This conventional device includes a right-side camera and a left-side camera, which are horizontally spaced apart from each other by a predetermined distance at a predetermined position of a vehicle, and a right-side frame memory and a left-side frame memory that temporarily store image signals from these cameras. have. These frame memories are composed of a plurality of pixels, and the image signal stored in one of the right side frame memory and the left side frame memory is referenced to detect the edge point of the object based on the brightness difference between adjacent pixels.

With the image signal of one of the frame memories as a reference, the image signal of the other frame memory is superimposed on the image signal of the other frame memory while sequentially shifting its position and the superimposed state. The difference between both image data in is calculated.
Then, the shift amount that minimizes this difference is acquired as the parallax between both cameras, and the relative distance between the object and the camera is calculated based on this parallax.

In such a conventional apparatus, the image signal to be superimposed contains an image of height "0" (on the road surface), for example, a white line, a character or a pattern drawn on the road surface. An image on such a road surface is also a calculation target. However, since the image on the road surface does not hinder the traveling of the vehicle, the detection operation for the image on the road surface is unnecessary processing. There is a problem that the processing time becomes long due to the unnecessary processing.

In order to solve this problem,
The applicant of the present application, in Japanese Patent Application No. 6-42433 (hereinafter referred to as prior application device), extracts only the object image by removing the image on the road surface and detects the edge of the extracted object image. Then, we proposed a vehicle periphery monitoring device that recognizes the position of an object based on this edge. The prior application device will be described below.

This prior application device has a device configuration shown in FIG. In the figure, 1 is an image pickup unit as an image pickup unit, 2 is a steering angle detection unit that outputs turning information of a vehicle, 3 is a storage unit that stores image information and the like, 4 is a data processing unit that executes various calculation processes, 5 Is a display unit for displaying the position of the obstacle or a message, and 6 is a voice instruction unit for generating an alarm sound or voice guidance.

The image pickup section 1 is a right CCD camera 11R.
And the left CCD camera 11L and the right CCD camera 11
It has a right side image plane 12R for projecting the image information picked up by the R and a left side image plane 12L for projecting the image information picked up by the left CCD camera 11L. As shown in FIG. 15, the image pickup unit 1 is attached to the rear of the vehicle at a position of height H at the rear center of the vehicle 100. The pair of CCD cameras 11R and 11L forming the image pickup unit 1 are attached at a predetermined distance in parallel with each other at a depression angle θ _S. As a result, the image pickup unit 1 is provided in the monitoring area 1 behind the vehicle.
00a [100a (11R) and 100a (11L)]
Image.

The steering angle detector 2 includes a steering wheel angle sensor for detecting the amount and direction of rotation of the steering wheel, a steering angle sensor for detecting the steering angle of the steered wheels (generally the front wheels) (neither is shown), and the like. The turning direction of the vehicle is output as turning information based on detection signals from these sensors. The storage unit 3 includes the right image plane 12 of the imaging unit 1.
A right frame memory 31R that temporarily stores the image information projected on R as a right image signal, a left frame memory 31L that also temporarily stores the image information projected on the left image plane 12L as a left image signal, and a right frame memory 31L. A right-side corrected image memory 32R and a left-side corrected image memory 32L that hold corrected image information obtained by performing a predetermined correction process on each of the image signals stored in the left-side frame memories 31R and 31L, and a difference image, a differential image and Difference image memory 3 that holds each edge image
3, a differential image memory 34 and an edge image memory 35. Each of these memories 31 to 35 has a structure of m rows and n columns, and is configured as a memory of 512 pixels (m) × 512 pixels (n), for example. Then, in each pixel forming this memory, for example, luminance value data of 256 gradations is stored.

The data processing unit 4 has a ROM 42 in which an operation program is stored, a CPU 41 which operates according to this operation program, and a RAM 43 which temporarily stores information required when the CPU 41 operates. The display unit 5 has a display 51, and the display 51
Is based on the display image signal output from the CPU 41,
It displays the relative position of the object to the vehicle or displays a message to the driver. The voice instruction unit 6 is
Based on the buzzer sound signal or the voice guidance signal output from the CPU 41, the speaker 61 outputs the buzzer sound or the voice guidance.

In the prior application device having such a configuration, an object (obstacle) is detected and the relative position between the object and the vehicle is calculated based on the video signal from the image pickup section 1. First, the image capturing process by the image capturing unit 1 will be described.
The video signal picked up by the image pickup unit 1 is once projected onto the image planes 12R and 12L, and then stored in the right frame memory 31R and the left frame memory 31L as image information, that is, as brightness value data for each pixel. The image information stored in the right frame memory 31R and the left frame memory 31L indicates the distortion aberration of the lens of the right CCD camera 11R and the left CCD camera 11L (hereinafter, simply referred to as the CCD camera 11). It is an included image. This distortion aberration causes an error in detecting the position of the object, which will be described later.

That is, considering a case where a lattice pattern is imaged, when the lens of the CCD camera 11 has no aberration, the lattice pattern is stored in the frame memory 31 as it is as shown in FIG. It Also,
When the lens has an aberration, as shown in FIG. 14 (b), an image in the center of the optical axis is distorted into a barrel shape bulging outward, or as shown in FIG. 14 (c). An image in which the image at the center of the optical axis is distorted into a pincushion curved inward is stored in the frame memory 31.

Then, the data processing unit 4 operates as shown in FIG.
(B) or corrected image information is generated by performing a correction process on a distorted image as shown in FIG.
This corrected image information is stored in the right side corrected image memory 32R and the left side corrected image memory 32L. This corrected image information is also stored as brightness value data for each pixel, as in the above image information. The process of correcting the distortion of the image will be described below.

As shown in FIG. 14D, the point P (x ₀ , y ₀ ) when there is no distortion is point P'due to the distortion.
Assuming that an image is formed at (x, y), the aberration amount D can be expressed by the following equation (1). _{D = [(x 0 -x)} 2 + (y 0 -y) 2] 0.5 ··· (1)

Then, FIG. 14B or FIG.
In the distorted image as shown in (c), the aberration amount D increases in proportion to the cube of the distance from the optical axis. That is, since it is proportional to the cube of the distance from the center point of the lens to the point P, the right side of the above equation (1) can be expressed by the following equation (2). [(X ₀ −x) ² + (y ₀ −y) ² ] ^0.5 = k ₁ [(x ₀ ² −y ₀ ² ) ^0.5 ] ³ (2) In the above formula, k ₁ is determined by the lens. Proportional constant

Therefore, when the lens has distortion, the distortion can be corrected by, for example, performing the calculation of the following equation (3). x ₀ ≈x (1-k ₁ (x ² + y ² )) y ₀ ≈y (1-k ₁ (x ² + y ² )) (3)

By the way, when the distortion aberration of the image is corrected by the calculation of the equation (3), the distance between the adjacent pixels becomes large and the image may be omitted. The data processing unit 4 interpolates this missing image based on the information of the adjacent pixels. Then, the image information that has undergone such correction processing and interpolation processing is corrected image information as the right corrected image memory 32R and the left corrected image memory 3
It is stored in each 2L. Thus, the image capturing process by the image capturing unit 1 is completed.

Next, the data processing unit 4 calculates the position in the captured image based on the corrected image information,
The background image (image of height “0”) is removed, and the edge image of the object is generated. Hereinafter, these processes will be described.

First, the process of calculating the position based on the captured image will be described. As described with reference to FIG. 15, the image pickup unit 1, that is, the CCD camera 11 is attached at a predetermined position behind the vehicle at an installation depression angle θ _S and picks up an image of the monitoring area 100a. Therefore, the image captured by the image capturing unit 1 is an image based on this predetermined position, and the position calculated from this captured image is also the position based on this predetermined position. Therefore, in order to facilitate the following description, as shown in FIG. 16, the coordinates based on this predetermined position, that is, the camera installation position are X ', Y', Z '.
The coordinates with respect to the road surface are represented by X, Y, Z.

In the X ', Y', Z'coordinate system with the camera installation position as a reference, the Z'axis is defined as the lens optical axis of the CCD camera 11, as shown in FIG. , The X'axis is defined as an axis parallel to the road surface, and the Y'axis is defined as an axis orthogonal to both the Z'axis and the X'axis. Therefore, the right CCD camera 1
The 1R and the left CCD camera 11L are arranged such that their lens optical axes coincide with the Z ′ axis. Also,
With respect to the X'-axis, the center points of the respective lenses are arranged on the X'-axis and the distances dxa from each other.
Are spaced apart. In order to facilitate the following description, the origin O of the X ′, Y ′ and Z ′ axes will be defined as the center of the lens of the left CCD camera 11R.

CCD camera 11 installed as described above
Point P (X _P ′, Y _P ′, Z _P ′) imaged by
Is held as P _R (x _RP , y _RP ) in the right side correction information memory 32R, and P is stored in the left side correction information memory 32L.
It is held as _L (x _LP , y _LP ).

The Z ′ coordinate Z _P ′ of this point P is shown in FIG.
As shown in the schematic view in the X′Z ′ plane of 7 (b),
It can be determined by the similarity of triangles. That is, this distance Z _P ′ can be expressed by the following equation (4). Z _P ′ = dxa · f / (x _LP −x _RP ) ... (4) In the above formula, dxa is the distance between both lenses, and f is the focal length of the lenses.

Similarly, for the X ′ coordinate X _P ′ of the point P,
As shown in the schematic view of the X′Z ′ plane of FIG. 17B, it can be obtained by similarity of triangles. And Y'of point P
The coordinates Y _P ′ can also be obtained in the same manner by assuming a Y′Z ′ plane (not shown). In other words, these points P X 'coordinate X _P' and Y 'coordinate Y _P'
Can be calculated by the following equations (5) and (6), respectively. _{X P '= Z P' x} LP / f = dxa · x LP / (x LP -x RP) ··· (5) Y P '= Z P' y LP / f = dxa · y LP / (x LP -X _RP ) ... (6) Regarding the coordinate X _P ′, the reference coordinate is the right CC
When the distance is between the D camera 11R and the left CCD camera 11L, the difference of 1/2 of the coordinate X _P ′ calculated by the above equation (5) and the distance dxa between both lenses may be taken.

A point P (X _P ′, Y _P ′, Z in the X′Y′Z ′ coordinate system calculated by the above equations (4) to (6).
_{Since P} ') is the coordinate value of the coordinate system with the camera installation position as the reference as described above, it is necessary to convert this coordinate value into the coordinate value in the XYZ coordinate system with the road surface as the reference. In this case, if the depression angle of the image pickup unit 1 (CCD camera 11) is θ _S , the coordinates (X _P ′, Y _P ′, Z _P ′) of the point P at the X′Y′Z ′ coordinates and the road surface. XYZ based on
The relationship with the coordinates is as shown in FIG.

Therefore, the coordinates (Z _P ′, Y _P ′, _XP ′) calculated by the above equations (4) to (6) are converted into XYZ coordinates by executing the following equations (7) to (9). It can be converted into the coordinates (X _P , Y _P , Z _P ) of the point P in the system. _{X P = X P '··· (} 7) Y P = H-Z P' cos θ S + Y P 'sin θ S ··· (8) Z P = Z P' sin θ S + Y P 'cos θ S ... (9)

Next, the object recognition processing by the data processing unit 4 will be described. First, the removal process of the background image (image of height “0”) will be described. FIG.
(A) shows the right-side corrected image stored in the right-side corrected image memory 32R after being subjected to the above-described distortion aberration correction after being picked up by the right-side CCD camera 11R. In the figure, 300 is a white line drawn on the road surface, and 200 is a pole-shaped object. Here, it is assumed that all the right-side corrected images stored in the right-side corrected image memory 32R are background images having a height of "0", that is, images drawn on the road surface. Then, based on the right-side corrected image assumed in this way, conversion processing is performed so that this right-side corrected image becomes an image (projected image) taken at the image pickup position of the left CCD camera 11L [FIG. 18 (b)].

The conversion process of the projected image will be described below. Here, the point of the projection image corresponding to the point P _R (x _RP , y _RP ) of the right image is P _L ′ (x _LP ′, y _LP ′).
As shown in FIG. 16, the X ′ axis of the camera coordinates and the X axis of the road surface coordinates are parallel, and the x axes of the scanning lines imaged by the camera (x _L axis and x _R axis in FIG. 17) are also parallel. , Y of the captured image when the same object is captured.
_{The L} and y _R values match. If all the images are on the road surface, the value of Y _P shown in the above equation (8) is zero.
From the above, the following equations (10) and (11) can be derived. Then, by substituting equation (11) Z _P 'Y _P and of the formula (6)' of the formula (4) Z _P 'and Y _P' of, as shown in equation (12), x _LP ' Can be asked.

Y _LP ′ = y _RP (10) 0 = H _P −Z _P ′ cos θ _S + Y _P ′ sin θ _S (11) x _LP ′ = (dxa · f cos θ _S −dxa · Y _RP sin θ _S ) / H + x _RP (12) The data processing unit 4 creates a projection image [FIG. 18 (b)] by performing the operations of the above equations (10) and (12). To do.

Then, when the projection image thus created is superimposed on the left side corrected image, it becomes as shown in FIG. 18 (c). That is, when the image captured by the right CCD camera 11R is projected, the pattern such as a white line drawn on the road surface matches the pattern captured by the left CCD camera 11L in position and brightness, and the object is higher than the road surface. The greater the difference, the greater the difference. Therefore, by taking the difference between the left image data and the projection image data, the brightness value of the pixels forming the road surface other than the pixels forming the object having a height becomes a value "0" or a value close to "0". . If the value equal to or smaller than the predetermined threshold value is set to "0", all values are set to "0". In this way, by taking the difference of the projection image data and left image data, the differential image as shown in FIG. 18 (d), (background image height "0") the road surface image is removed, the high Only the portion with the depth is extracted as a value other than the value “0”. Then, this difference image is stored in the difference image memory 33 of the storage unit 3.

By the way, the projected image contains an error.
The difference image [Fig. 18 (d)]
In some cases, the road surface image may remain. this
Therefore, a difference image between the projected image and the left-side corrected image is generated.
In that case, the following processing is performed. That is, FIG.
As shown in (a) and (b), the brightness of each pixel of the projected image
Degree value I₁~ I₇The brightness of each pixel of the left-side corrected image corresponding to
Value I₁'~ I ₇′ Is calculated sequentially, and the difference value is predetermined
Value I₀The above pixels [pixel I_FiveEquivalent to]
Is the pixel I as shown in FIG._FiveAdjacent to ′
Pixel I_Four'And I₆Find the difference with ′. And that
Minimum value of difference (pixel I in FIG._FourThe difference value from ′)
The difference value with respect to the prime.

In this way, the background image of height "0" in the captured image is removed, and only the image with height, that is, the image of the object is extracted. Following this, edge extraction processing is performed on the extracted object image. Next, this object edge extraction processing will be described.

This object edge extraction processing is performed based on the image information stored in the left side corrected image memory 32L. That relates to the left correction image stored in the left corrected image memory 32L, X luminance value I _m of the image data of the m rows and n _columns, the _n in the horizontal direction, that is 16 '
Scanning is performed in the axial direction, and a differential image is generated by the calculation of the following expression (13). | I _{m, n + 1} −I _{m, n} | ≧ E _0, then E _{m, n}
= 1 | I _{m, n + 1} −I _{m, n} | <E _0, then E _{m, n}
= 0 (13) In the above formula, E ₀ is a threshold value

As shown in FIG. 20B, this differential image is an image in which the vertical edge portion of an object or a character drawn on the road surface is "1" and the other portions are "0". Becomes Then, this differential image is stored in the differential image memory 34 of the storage unit 3. The differential image obtained in this way [FIG. 20 (b)] and the differential image generated by the above-described road surface image removal processing and held in the differential image memory 33 [FIG.
When (d)] is overlaid and the AND operation is performed, an object edge image in which only the edge portion of the object shown in FIG. 20C is extracted is generated. This object edge image is stored in the edge image memory 35.

Then, the data processing unit 4 recognizes the object based on the object edge image stored in the edge image memory 35 and calculates the relative position between the object edge and the vehicle. Further, it predicts the course of the vehicle from the turning information of the vehicle, predicts a collision between the object recognized based on the predicted course and the vehicle, and issues a warning or the like to warn the driver when necessary.

[0034]

In such a prior application device, the background image having the height of "0", that is, the road surface image is removed based on the video signal picked up by the image pickup unit 1 to remove the object image. Since it is configured to generate an edge image and calculate the relative position between the object and the vehicle based on the generated edge image, there is an advantage that unnecessary calculation processing can be omitted and the processing can be speeded up, which is a good method. .

By the way, in this prior application device, the right side CC is used as a parameter for performing the various calculations described above.
Center of lens of D camera 11R and left CCD camera 11L
The arrangement distance dxa of the lens centers, the focal length f of each of these lenses, the installation height H of the CCD camera 11, the installation depression angle θ _S of the CCD camera 11 and the like are used. And the above C
With respect to the CD camera 11, when there is a difference in the focal length f, that is, the image pickup magnification, between the right CCD camera 11R and the left CCD camera 11L, the size of the subject in the image information picked up by each of them is different, and as described above. The background image could not be removed. As a countermeasure, CCs with the same characteristics are selected from a plurality of CCD cameras.
Although the method of selecting the D camera 11 has been performed, this method requires the trouble of selecting the CCD camera 11 and a large number of CCDs.
It was not economical because I needed to prepare a camera.

Further, when the above-mentioned parameters (hereinafter referred to as installation parameters) are deviated, a difference between the coordinate values calculated by calculation and the actual coordinate values results in a detection error. Then, the background image of the height “0” that should be originally recognized as the “road surface image” is recognized as an object with a height, that is, an “obstacle”. Therefore, in order to make this installation parameter a constant value, the vehicle 10 of the imaging unit 1
It was necessary to accurately attach to 0, and it took time to attach. Further, even if the image pickup unit 1 is accurately attached to a predetermined position of the vehicle 100, the attachment position is displaced with the passage of time, and thus it is difficult to maintain the installation parameter at a constant value.

As described above, in this prior application device,
There was room for further improvement in the above points. Therefore, in view of such an improvement, it is a main object of the present invention to provide a vehicle periphery monitoring device capable of preventing a background image erasing failure due to a variation in focal length of a characteristic of a CCD camera. Another object is to provide a vehicle periphery monitoring device capable of preventing an erroneous recognition of a road surface image due to variation and accurately extracting an object.

[0038]

A vehicle periphery monitoring device made according to the present invention to solve the above problems will be described with reference to the basic configuration diagram of FIG. That is, the vehicle periphery monitoring device of the present invention is based on the image information from the image pickup means 1 provided with the right side image pickup means 11R and the left side image pickup means 11L which are arranged at a predetermined position of the vehicle and are separated by a predetermined distance. In the vehicle periphery monitoring device that monitors the periphery of the vehicle,
An image holding unit 31 having a right side image holding unit 31R holding the right side image information from the right side imaging unit 11R and a left side image holding unit 31L holding the left side image information from the left side imaging unit 11L, and the right side image By scaling the image information of at least one of the image information and the left image information, the image information is scaled up and down so that the size of the subject in this one image information and the size of the subject in the other image information match. The magnification correction means 41a and the magnification correction means are used to
One of the image information whose size is
Is a background image with a height of "0", and
One of the specified image information captures the other of the image information
The image information is captured at the image capturing position of the image capturing means.
As described above, projection image information obtained by coordinate-converting one of the image information
Is output, and the projection image information matches the size of the subject.
Output the difference from the other image information as the object information.
Held by the object extracting means 41b and the image holding means.
A differential image in which an edge in the image information is detected, and the object
Image information obtained by overlaying information with AND
It is characterized in that an object existing around the vehicle is recognized based on the object edge detecting means 41c which outputs the information and the object information and the object edge information.

Further, the magnification correction means 41a includes a target image determination means 41e for determining image information to be magnification-converted based on image information from the right side image pickup means 31R or the left side image pickup means 31L, and the target image determination means. 41
and a correction value acquisition unit 41f that acquires the conversion magnification k ₃ for the image information that is the magnification conversion target by e.

Further, the target image determination means 41e selects image information having a high image pickup magnification as a magnification conversion target, and the correction value acquisition means 41f reduces the image information selected as a magnification conversion target. I am trying.

The correction value acquisition means 41f also corrects the correction value based on the parallax information between the plurality of points of interest in the right side image information and the plurality of points of interest in the left side image information corresponding to the points of interest in the right side image information. It is characterized by determining.

The image pickup means 1 is placed at an arbitrary position on the vehicle.
A reference image projecting unit 7 for projecting a reference image serving as a reference for measurement is provided in the image pickup area of, and the magnification correcting unit 41a includes:
Image information from the imaging unit 1 based on the right side reference image acquired by the right side imaging unit 11R capturing the reference image and the left side reference image acquired by the left side imaging unit 11L capturing the reference image. It is characterized by performing enlargement / reduction correction.

[0043] Further, based on the image information from the right-side imaging unit 11R or the left image pickup means 11L, the right
Imaging by the side imaging means 11R and the left imaging means 11L
The actual parallax of the captured image is obtained, and the image pickup means 1 is installed.
Theoretical parallax obtained based on the fixed parameters and the obtained actual parallax.
Parallax correction that outputs the difference from the parallax as parallax correction information
Means 41g is provided , and the object extracting means 41b is configured to perform the above-mentioned operation based on the parallax correction information from the parallax correcting means 41g.
The feature is that the projection image information is corrected .

Also, an object position calculating means 41d for calculating the position of the object based on the image information held in the image holding means 31 by utilizing the object edge detected by the object edge detecting means 41c, Display means 5 for displaying the relative position between the vehicle and the object is provided, and the driver is informed of the relative position between the vehicle and the object based on the position information of the object output from the object position calculation means 41d. Is characterized by.

Further, an object position calculating means 41d for calculating the position of the object based on the image information held in the image holding means 31 by using the object edge detected by the object edge detecting means 41c, Route prediction means 41h for predicting the route of the vehicle based on the turning information of the vehicle
And an alarm means 6 for issuing an alarm such as an alarm sound,
When the collision between the vehicle and the object is predicted based on the position information of the object output from the object position calculation means 41d and the predicted course information from the course prediction means 41h, and the "collision" is predicted, the alarm is issued. An alarm is generated by at least one of the means 6 and the display means 5.

[0046]

In the above structure, the magnification correction means 41a enlarges or reduces the image information so that the sizes of the subject imaged by the right side image pickup means 11R and the left side image pickup means 11L are matched, and the object extraction means 41b enlarges the magnification. Correction means 41
a of the image information in which the sizes of the subjects are the same
On the other hand, if all the images are background images of height "0"
And one of the image information thus assumed is
The image is captured at the image capturing position of the image capturing device that captures the other image information.
One of the image information is coordinated so that the image information becomes
The converted projection image information is output, and the projection image information and the
The difference between the image information of the same size of the subject and the other,
Output as object information. The object edge detecting means 41c
The edge in the image information held in the image holding means 31 is detected.
The differential image that was output and the object information are overlaid and the AND is taken.
The acquired image information is output as object edge information . Then, the object existing around the vehicle is recognized from the object information and the object edge information. That is, since the means for correcting the difference in the image pickup magnification of the image pickup means 1 is provided, it is possible to make the difference in the size of the subject due to the difference in the focal length of the image pickup means 1 the same, and the error of the road surface image based on the installation state. You can eliminate recognition. As a result, the object image can be accurately extracted.

The target image determination means 41e determines the image information to be scaled based on the image information from the right side image pickup means 31R or the left side image pickup means 31L, and the correction value acquisition means 41f determines the scale factor by the target image determination means 41e. The conversion magnification for the image information to be converted is acquired. That is, since the conversion magnification is acquired based on the image information from the image pickup means 1 in correcting the image pickup magnification of the image pickup means 1, the apparatus can be easily configured.

The target image determination means 41e selects image information having a high image pickup magnification as a magnification conversion target, and the correction value acquisition means 41f performs reduction conversion on the image information selected as a magnification conversion target, thereby the other image information. The same as the imaging magnification of. That is, since the image information on the imaged side is greatly reduced and converted, it is possible to reduce the disturbance of the image due to the magnification conversion of the image.

The correction value acquisition means 41f determines the correction value based on the parallax information between the plurality of points of interest in the right side image information and the plurality of points of interest in the left side image information corresponding thereto. That is, since the magnification correction is performed according to the interval between the coordinate points to be measured, the processing can be performed at high speed without requiring complicated calculation processing.

The reference image projection means 7 projects a reference image serving as a reference for measurement in the image pickup area of the image pickup means 1, and the magnification correction means 41a projects the reference image on the right side image pickup means 11R.
The image information from the image pickup means 1 is enlarged or reduced based on the left side reference image obtained by the left side image pickup means 11L taking the right side reference image and the reference image obtained by the image pickup by the left side image pickup means 11L. That is, since the means for projecting the reference image for magnification correction is provided, the correction operation can be performed at any time.

The parallax correction means 41g is the right side image pickup means 1
Based on 1R or image information from the left image pickup means 11L, the said right image pickup means 11R left imager 1
The actual parallax of the image captured by 1L is calculated, and
The theoretical parallax obtained based on the installation parameters of the image pickup means 1
And the difference between the above-obtained actual parallax is output as parallax correction information.
Force The object extraction means 41b corrects the projection image information based on the parallax correction information from the parallax correction means 41g .
It That is, since the means for calculating the correction information regarding the installation state of the image pickup means 1 is provided, it is possible to eliminate the erroneous recognition of the road surface image based on the installation state, and to accurately extract the object image. Further, the relative position between the vehicle and the object can be calculated with high accuracy.

The object position calculating means 41d calculates the relative position between the object and the vehicle based on the object edge information from the object edge detecting means 41c and the image information held in the image holding means 31. The display means 5 informs the driver of the relative position of the object detected based on the relative position information of the vehicle and the object. That is, since the means for calculating the relative position of the detected object with respect to the vehicle and the means for displaying this object are provided, it is possible to inform the driver of the relative position of the detected object with respect to the vehicle.

When the route predicting means 41h predicts the course of the vehicle based on the turning information of the vehicle, the display means 5 or the warning means 6 predicts that the predicted vehicle course and the object "collide". Generate an alarm. Therefore, an accident such as a collision with an object can be prevented.

[0054]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A vehicle periphery monitoring device of the present invention will be described below with reference to the drawings. The vehicle periphery monitoring device according to the present invention has substantially the same configuration as the prior application device described in FIG. That is, as shown in FIG. 2, an imaging unit 1 having a right CCD camera 11R, a left CCD camera 11L, and the like, and a steering angle detection unit 2 configured as a steering wheel steering angle sensor or a steering angle sensor to output vehicle turning information. , Right frame memory 31R, left frame memory 31L, right corrected image memory 32R, left corrected image memory 32L,
A data processing unit 4 including a storage unit 3 including a differential image memory 33, a differential image memory 34, and an edge image memory 35, a CPU 41 that operates according to an operation program, a ROM 42 that stores the operation program, and a RAM 43 that temporarily stores necessary information. And a display unit 5 for displaying a relative position between the object and the vehicle and a message to the driver, and a voice instruction unit 6 for outputting a buzzer sound or voice guidance to the driver. An image projecting unit 7 that projects the reference image onto the road surface is provided.

This image projection unit 7 is incorporated in the image pickup unit 1 as shown in FIG. 7A, for example, and more specifically, it is arranged substantially in the center between the right CCD camera 11R and the left CCD camera 11L. There is. Then, the image projection unit 7
Is a light bulb 71 as a light source, as shown in FIG.
a, the mask pattern 71b, and the lens 71c, the light from the light bulb 71a is made into linear light by the mask pattern 71b, and this linear light, that is, the reference image is projected onto the road surface via the lens 71c.

In the mask pattern 71b, a plurality of slits 711 to 715 are arranged horizontally with respect to the horizontal direction (the long side direction of the mask pattern 71b in the figure) and at different inclination angles according to the angle of view of the lens of the CCD camera 11. Has been formed. That is, the slit 713 in the central portion is formed parallel to the vertical direction (direction of the same short side), and the slits 712 and 714 adjacent to this slit 713 are formed so as to spread to the upper end side, and these slits 712 and 714 The slits 711 and 715 located on the outer side are formed to be inclined so that the upper end side further expands. In this way, the slits 711 to 715 are formed so as to be inclined at an angle such that the upper ends of the slits 711 to diverge, so that the linear light (reference image) from the image projection unit 7 becomes outward as it goes away. It becomes a spread light. When the linear light is imaged by the imaging unit 1, the linear lights are imaged as light parallel to each other, as described later.

As shown in FIG. 7C, the image projection unit 7 is a so-called fiber grating 72 in which a plurality of laser light sources 72a and a plurality of optical fibers are arranged in a plate shape.
b and the cylindrical lens 72c, the laser light emitted from the laser light source 72a may be branched by the fiber grating 72b and then projected onto the road surface as linear light through the cylindrical lens 72c.

As shown in FIG. 8, for example, such an image projection unit 7 has a plurality of linear lights 4 extending from the front side to the back side of the central portion of the image pickup area 100a of the image pickup section 1.
A reference image 400 composed of 01 to 405 is projected. Regarding the image projecting unit 7, the image projecting unit 7 is very simple in structure, and in this case, the image projecting unit 7 is arranged at an arbitrary position different from the image pickup unit 1 as indicated by a symbol A in FIG. be able to. Further, in this embodiment, one linear light 403 is arranged in the center and two linear lights 401, 402, 404 and 405 are arranged on both sides of the linear light 403. Is not limited to this, and can be set to an arbitrary number of 2 or more. In this case, for these linear lights,
For the convenience of magnification correction processing, which will be described later, they are arranged at equal intervals.

In the present invention, the ROM 42 described above is used.
The operation program stored in the above, that is, the processing operation by the data processing unit 4 is also different. Hereinafter, this processing operation will be described with reference to the flowcharts of FIGS. In this processing operation, first, a magnification correction operation is performed in step S310 in the flowchart of FIG. The magnification correction operation in step S310 is
Specifically, it is performed according to the flowchart of FIG.

That is, first in step S610,
The reference image is captured by the right CCD camera 11R and the left CCD camera 11L. That is, in this step S610, first, the reference image 400 in the monitoring area 100a by the image projection unit 7 described in FIG.
(Linear light 401 to 405) is projected. continue,
The reference image 400 projected by the right CCD camera 11R and the left CCD camera 11L of the image capturing unit 1 is captured. As a result, the right reference image information and the left reference image information are stored in the frame memory 31R and the frame memory 31L, respectively.

Then, the frame memories 31R and 3R
The distortion aberration correction process described in FIG. 14 is performed on the image information stored in 1L to generate the right reference image shown in FIG. 9A and the left reference image shown in FIG. 9B. These reference images are stored in the right side correction memory 32R.
And the left correction memory 32L. Note that, regarding the capture of the reference image in step S610, the case where the reference image projected by the image projecting unit 7 is used has been described in this embodiment, but the reference image drawn on the road surface is captured as described above. Good. In this case, it is necessary to go to a factory or the like every time the image pickup unit 1 is corrected, but by providing the reference image projection unit 7 as in the present embodiment, this correction process can be performed at any time.

Then, in the following step S620,
Based on the left and right reference images acquired in step S610, the coordinate values of the target point group in these right and left reference images are acquired. Specifically, in this step S620, as shown in FIG. 9, the intersection point coordinates P _{Rc1 to} P _Rc5 of the scanning line 41c and the left edge of the right side reference images 401R to 405R, the scanning line 41c and the left side reference images 401L to 405L. Intersection P with the left edge at
Acquisition of _{Lc1 to} P _Lc5 is performed. Then, after acquiring the coordinate values of each target point group, the process proceeds to step S621.

In step S621, an image to be scaled is determined. In this embodiment, an image having a higher image pickup magnification, that is, an image on which a subject is imaged larger is selected as a magnification conversion target image, and this target image is reduced and corrected in a subsequent process. This is because the resolution of the image is taken into consideration, and it is easier to obtain a high image quality by reducing and correcting an image captured in a larger size than by enlarging and correcting an image captured in a small size. However,
In this step S621, an image captured in a small size may be set as a target image, and the target image may be enlarged and corrected in a subsequent process.

The determination of this target image is made in the above step S6.
It is performed based on the intersection coordinates acquired in 20. For example,
9A, the difference value between the intersection point coordinates P _RC1 of the reference image 401R and the intersection point coordinates P _RC3 of the reference image 403R, and FIG.
The difference value of the intersection point coordinates P _LC1 of the reference image 401L of (b) and the intersection point coordinates P _LC3 of the reference image 403R is compared, and the one having a larger difference value, that is, the one where the intervals between the reference lights are larger (in this example, 9A] is determined as an image with a high imaging magnification. Regarding this determination process, in the above example was compared with the interval of the reference image 401 and 403, is good, also compares the farthest is the reference image with each other as the reference image 401 and 405 as the reference image adjacent to each other so May be. When the determination process of step S621 ends, the process proceeds to step S630.

In step S630, the magnification correction value k ₃ for the target image is determined. In this step S630, in the case of the first correction value determination operation, the magnification correction value k ₃
Is set to a value “1.000”, and in the case of the second and subsequent correction value determination operations, that is, when it is determined to be “N” in step S640 described later, this magnification correction value k ₃ is set to a value larger than the previous magnification correction value. The value is obtained by subtracting "0.001". For example, in the correction value determining operation of the third time, the second magnification correction value "0.999" from the value "0.001" by subtracting the value "0.998" is the magnification correction value k _3. This is 2
Since One difference of the focal length of the CCD camera is about 1.000 to 0.985 in the magnification correction value k _3, such so-called "trial and error" in terms of processing speed and accuracy in the process sufficient for This is because things can be obtained. In addition, in the process of step S630, the magnification correction value k ₃ may be calculated based on the parallax between the right reference image and the left reference image. When the correction value determination process of step S630 ends, the process moves to subsequent step S631.

In step S631, the above step S6 is performed.
Enlargement / reduction processing (reduction processing in this embodiment) of the target image is performed based on the magnification correction value k ₃ determined in 30. As shown in FIG. 11A, this enlarging / reducing process is performed on the target image before correction which sets the optical axis (0, 0) as the origin at the center and sets it as the coordinate system of i, j. , And is multiplied by the magnification correction value k ₃ calculated in step S630. That is, in step S631, the following equation (14) is applied to the target image.
And execute equation (15). I _PO = i _PO × k ₃ (14) J _PO = j _PO × k ₃ (15) In the above equation, i _PO and j _PO are the coordinate values I _PO and J _PO of the uncorrected image. Coordinate value of the corrected image

By this processing, as shown in FIG. 11B, the image before correction is the image of the coordinate systems I and J after correction, that is, the original image frames (32a to 32d) shown by the dotted lines in the figure. The image is converted into an image in the converted image frame (32a 'to 32d'). As described above, in this embodiment, the reduction correction is performed on the reference image having a high imaging magnification, and thus the reduction-converted right reference image is generated by the process of step S631. Then, the process proceeds to S632.

In step S632, the above step S6 is executed.
The parallax value between the corresponding coordinate point pairs in the reference image (target image) that has been subjected to the scaling correction in 31 and the other reference image is acquired. That is, in this step S632, first, the right reference image that has been reduced and converted as shown in the schematic diagram of FIG. 12A is superimposed on the left reference image, and the original image frame is displayed as shown in the schematic diagram of FIG. 12B. Or the converted image frame, whichever is smaller. [In this embodiment, the converted image frame (32
a'-31d ')], the reference image 4 from the right CCD camera 11R for the image in this frame.
01R and the reference image 401 from the left CCD camera 11L
L, reference image 402R and reference image 402L, ..., Parallax 421 to 4 between reference images corresponding to each other.
Get 25. Then, the process proceeds to step S640.

In step S640, the above step S6 is executed.
It is determined whether the parallaxes 421 to 425 acquired in 32 match. In this step S640, parallax 421-
The average parallax of 425 is calculated, and the variation for this parallax is calculated. If the variation is within the predetermined range, it is determined as “match”, that is, “Y”, and the process proceeds to step S650. If the variation of the parallax value is outside the predetermined range, it is determined as “non-coincidence”, that is, “N”, and step S630.
Then, the process proceeds to and the scaling process of the target image is executed again. Regarding this determination process, a threshold value is set in advance, and if the deviation from the average value of each parallax value is within this threshold value, “match”, and if it exceeds the threshold value, “non-match” Match "
It may be configured to determine that.

Then, in step S650, the magnification correction value k ₃ determined to be "match" in step S640 is stored in the RAM 43 of the data processing unit 4, and a series of processes is terminated, and the steps in the flowchart of FIG. S31
Move to 1. In the magnification correction operation described with reference to the flowchart in FIG. 5, a blank portion is formed around the peripheral portion of the reference image which is the magnification correction target and the other reference image, for example, the original image frame 32a shown in FIG. While part of the difference 32d and the converted image frame 32a'~32d' occurs, as described above, the magnification correction value k ₃ in an actual device is about 1.000 to 0.985, the correction magnification Since it is very small, the inconvenience of the processing due to this blank portion does not occur in the subsequent processing.

Then, in step S311, a "0" correction value acquisition operation is performed. The "0" correction value acquisition operation in step S311 is specifically performed by the flowchart of FIG.

That is, first in step S510,
Reference images are captured from the right and left CCD cameras 11R and 11L. That is, this step S
At 510, as described with reference to FIG. 8, the image projection unit 7 projects the reference image 400 in the monitoring area 100a. Next, the right CCD camera 11 of the image pickup unit 1
The reference image 400 projected by the R and left CCD camera 11L is captured. As a result, the right reference image information and the left reference image information are stored in the frame memory 31R and the frame memory 31L, respectively.

Then, the frame memories 31R and 3R
By performing the distortion aberration correction processing described in FIG. 14 on the image information stored in 1L, the right reference image shown in FIG. 9A and the left reference image shown in FIG. 9B. Is generated, and further, step S62 in the flowchart of FIG.
By multiplying the magnification correction target image determined in 1 by the magnification correction value similarly stored in step S650, the sizes (imaging magnification) of both reference images are made equal. These reference images having the same imaging magnification are stored in the right side correction memory 32R and the left side correction memory 32L, respectively. When this step S510 ends, step S52
Move to 0.

In step S520, the above step S5 is performed.
Based on the left and right reference images acquired in 10, the coordinate values of the point of interest in the reference image are acquired for each of the left and right reference images. Specifically, the intersection coordinates of the left edge of the right reference image 403R and the scan line 41 n in FIG. 12B are acquired as P _RO (x _RPO , y _RPO ) and the left edge of the left reference image 403L and the scan line are acquired. The intersection coordinates with 41n are acquired as P _LO (x _LPO , y _LPO ). Then, such coordinate acquisition operation is sequentially performed from the scanning line 41a at the upper end to the scanning line 41b at the lower end to acquire a group of intersection coordinates, and step S530.
Move to.

In step S530, the above step S5 is performed.
The right CCD camera 11R is calculated by the following equation (16) for each intersection coordinate of the intersection coordinate group acquired in 20.
And the parallax (actual parallax) D _ac of the image captured by the left CCD camera 11L is calculated, and the process proceeds to step S540. D _ac = x _LPO −x _RPO (16)

In step S540, the theoretical parallax D _th based on the installation parameters of the image pickup section 1 is calculated. This theoretical parallax D _th, that is, x _LP ′ −x _RP can be calculated by the calculation of the following expression (17) derived based on the above expression (12). D _th = x _LP ′ −x _RP = (dxa · fcos θ _S −dxa · y _RP sin θ _S ) / H (17) When the theoretical parallax is calculated in step S540, the process proceeds to step S550. To do.

In step S550, the above step S5 is performed.
The “0” correction value k ₂ is calculated from the difference between the actual parallax D _ac calculated in step S30 and the theoretical parallax D _th calculated in step S540, that is, the following equation (18). k ₂ = D _ac −D _th (18) Then, the calculated “0” correction value k ₂ is stored in the RAM 43 of the data processing unit 4, and a series of “0” correction value acquisition operation is completed. The process moves to step S320 in the flowchart of FIG.

In step S320, the right side C of the image pickup unit 1
Video information from the CD camera 11R and the left CCD camera 11L is used as right image information and left image information, respectively, the right frame memory 31R and the left frame memory 31.
Store in L and move to step S330. The image information acquired in step S320 is the image information in the monitoring area 100a.
This is for obtaining obstacles in 00a. Therefore, the above step S320 (flow chart of FIG. 5)
It is an image different from the reference image acquired in. Then, in step S330, a corrected image is generated. That is, the image information held in the right frame memory 31R and the left frame memory 31L is read, the distortion aberration correction process described in FIG. 14 is performed on the read image information, and the process proceeds to step S621 in the flowchart of FIG. For the magnification correction target image determined by
Similarly, by multiplying the magnification correction value stored in step S650, the imaging magnification correction process for the image information is performed. Then, the corrected image information thus corrected is stored in the right side corrected image memory 32R and the left side corrected image memory 32L, respectively, and the process proceeds to step S340. With respect to the edge portion of the image, the corresponding points of the left and right images of the object to be measured are extracted from the right correction image memory 32R and the left correction image memory 32L, and the process proceeds to step S390.

In step S340, with respect to the left side corrected image stored in the left side corrected image memory 32L, the above equation (1
The differential image [FIG. 20 (b)] for the left side corrected image is generated by performing the calculation process of 3), and the generated differential image is stored in the differential image memory 34. Then, the process proceeds to step S350. In step S350, the projection image creation process described in FIG. 18, that is, it is assumed that all the heights of the right side corrected images stored in the right side corrected image memory 32R are “0” and the coordinate conversion process is performed on the right side corrected image. And left side CCD camera 11L
A projected image [FIG. 18 (b)] imaged in step 1 is created.

In step S350, the projection image in which the variation in the installation parameters of the image pickup unit 1 is corrected is created by using the "0" correction value k ₂ acquired in the flowchart of FIG. That is, this step S3
At 50, the following equations (19) and (20) are executed to create a projected image. y _LP ′ = y _RP (19) x _LP ′ = (dxa · fcos θ _S −dxa · y _RP sin θ _S ) / H + x _RP + k ₂ (20) When this step S350 ends Step S
Move to 360. In step S360, step S
Superimpose the projection image created in 350 on the left correction image [Fig.
8 (c)] and the difference between the two is taken to create a difference image [FIG. 18 (d)], and the created difference image is stored in the difference image memory 33. And step S
Move to 370.

In step S370, an object edge image creating process is performed. That is, the differential image stored in the differential image memory 34 in step S340 and the differential image stored in the differential image memory 33 in step S350 are superposed and the AND is performed to obtain the object edge image [FIG. )] Is generated. Then, the generated object edge image is stored in the edge image memory 35, and step S
Move to 380. In step S380, for the edge portion of the object edge image data created in step S370, the corresponding points of the left and right images of the object to be measured are corrected to the right corrected image memory 32R and the left corrected image memory 32L.
More extraction is performed, and the process proceeds to step S390.

In step S390, the above step S3 is performed.
16 for each coordinate point of the object edge extracted in FIG.
The three-dimensional position coordinate calculation operation described with reference to FIG. 17 is performed to calculate the three-dimensional coordinate values of this edge image. Then, in the coordinate position calculating operation in step S390, the “0” correction value k ₂ described in the flowchart of FIG.
Coordinates are calculated using. That is, this step S
In 390, the coordinate values Z _P ′, X _P ′, and Y _P ′ are calculated by executing the calculations of the following equations (21) to (23), and the calculated coordinate values are used to calculate the above equation (7). ) -Equation (9) is executed to obtain the coordinate values Z _P , X _P and Y _P, that is, the position information of the obstacle in the monitoring area 100a. Z _P ′ = dxa · f / (x _LP −x _RP + k ₂ ) ... (21) X _P ′ = dxa · x _LP / (x _LP −x _RP + k ₂ ) ... (22) Y _P ′ = Dxa · y _LP / (x _LP −x _RP + k ₂ ) ... (23) Then, when this step S390 ends, the process moves to step S410 shown in the flowchart of FIG.

In step S410, the data processing unit 4
Reads the turning information from the steering angle detector 2, for example, the steering angle information of the steering wheel. Then, the process proceeds to step S420. In step S420, the course of the vehicle is predicted based on the turning information read in step S410, and the predicted trajectory of the vehicle is calculated by adding the shape information of the vehicle to the predicted course. Then, the calculated predicted trajectory is stored in the RAM 43.
In step S430.

In step S430, the above-mentioned step S3 is performed.
Based on the obstacle information acquired at 90, the monitoring area 100
It is determined whether or not there is an obstacle in a. If it is determined in step 430 that “exists”, that is, “exists”, the process proceeds to subsequent step S440. On the other hand, if it is determined that “does not exist”, that is, “none”, the process proceeds to step S300 in the flowchart of FIG. Transition.

In step S440, the above step S4
Based on the predicted trajectory calculated in 20 and the obstacle position information calculated in step S430, it is determined whether there is a possibility of collision between the edge area of the obstacle and the vehicle. If it is determined that there is a possibility of collision, the process proceeds to step S441, and if it is determined that there is no possibility of collision, the process proceeds to step S442.

In step S441, the voice instruction unit 6 issues a buzzer sound or a voice guidance alarm to the driver, and the display unit 5 displays the predicted collision position between the vehicle and the obstacle and a message. Also,
In step S442, the relative position between the obstacle and the vehicle is displayed on the display unit 5. Then, these steps S4
41 and step S442, the series of processes is terminated,
The process moves to step S300 in the flowchart of FIG.
In step S300, it is determined whether or not to acquire the correction value in the next processing operation, that is, the magnification correction value k ₃ and the “0” correction value k _2, and if it is determined to “acquire”, that is, “Y”, updates the magnification correction value k ₃ proceeds to step 310, subsequently the process proceeds to step S311 to update the "0" correction value k _2. When it is determined that “not acquired”, that is, “N”, the process proceeds to step S320 and a series of processes is performed again. Magnification correction value k _{3 in} this case
And "0" correction value k ₂ uses the magnification correction value k ₃ and "0" correction value k ₂ up to the previous.

As is clear from the above description, the basic configuration of the present invention and the embodiments have the following correspondence. That is, the image pickup unit 1 is the same as the image pickup unit 1 in the embodiment, and the right side image pickup unit 11R and the left side image pickup unit 11L are each on the right side C.
The CD camera 11R and the left CCD camera 11L, the image holding means 31 in the frame memories 31R and 31L, the magnification correction means 41a in steps S610 to S650 in the flowchart of FIG. 6, and the object extraction means 41b in FIG.
Steps S340 to S360 in the flowchart of FIG.
Then, the object edge detecting means 41c similarly performs step S37.
0, the object position calculation means 41d similarly performs step S39.
Corresponds to 0.

The target image determining means 41e is in steps S620 to S621 in the flowchart of FIG. 6, the correction value obtaining means 41f is in steps S630 to S650 in the flowchart of FIG. 6, and the parallax correcting means 41g is step S510 in the flowchart of FIG. S550
The route prediction means 41h corresponds to S410 to S420 in the flowchart of FIG. 4, the display means 5 corresponds to the display unit 5, the alarm means 6 corresponds to the voice instruction unit 6, and the reference image projection unit 7 corresponds to the image projection unit 7. .

[0089]

As described above, according to the vehicle periphery monitoring apparatus of the present invention, since the means for correcting the difference in the image pickup magnification of the image pickup means 1 is provided, the object of the subject due to the difference in the focal length of the image pickup means 1 is provided. The size difference can be made the same and erroneous recognition of the road surface image based on the installation state can be eliminated. As a result, the object image can be accurately extracted.

Further, in correcting the image pickup magnification of the image pickup means 1, since the conversion magnification is obtained based on the image information from the image pickup means 1, the apparatus can be easily constructed.

Further, since the image pickup means 1 is constituted so as to reduce and convert the image information on the side which is greatly picked up, it is possible to reduce the disturbance of the image due to the magnification conversion of the image.

Further, since the magnification is corrected according to the interval between the coordinate points to be measured, the processing can be performed at high speed without the need for complicated calculation processing.

Further, since the means for projecting the reference image for magnification correction is provided, the correction operation can be performed at any time.

Further, since the means for calculating the correction information regarding the installation state of the image pickup means 1 is provided, it is possible to eliminate erroneous recognition of the road surface image based on the installation state, and it is possible to accurately extract the object image. Further, the relative position between the vehicle and the object can be calculated with high accuracy.

Since the means for calculating the relative position of the detected object with respect to the vehicle and the means for displaying this object are provided, the driver can be informed of the relative position of the detected object with respect to the vehicle. it can.

Further, means for predicting the course of the vehicle based on the turning information of the vehicle and means for issuing an alarm when it is predicted that the predicted vehicle course and an object "collide" are provided. Therefore, an accident such as a collision with an object can be prevented.

[Brief description of drawings]

FIG. 1 is a basic configuration diagram of the present invention.

FIG. 2 is a configuration diagram of an embodiment of the present invention.

FIG. 3 is an operation flowchart of the same embodiment.

FIG. 4 is an operation flowchart of the embodiment.

FIG. 5 is an operation flowchart of the embodiment.

FIG. 6 is an operation flowchart of the embodiment.

FIG. 7 is a diagram illustrating an image projection unit 7.

FIG. 8 is a diagram illustrating a reference image 400.

FIG. 9 is a diagram illustrating a magnification correction operation.

FIG. 10 is a diagram illustrating a magnification correction operation.

FIG. 11 is a diagram illustrating a magnification correction operation.

FIG. 12 is a diagram illustrating a magnification correction operation and a “0” correction value acquisition operation.

FIG. 13 is a block diagram of a prior application device.

FIG. 14 is an explanatory diagram of lens aberration correction in Examples and prior application devices.

FIG. 15 is an explanatory diagram of a mounting manner of the image pickup unit.

FIG. 16 is also an explanatory diagram of camera depression angle correction.

FIG. 17 is also an explanatory diagram of three-dimensional position measurement.

FIG. 18 is also an explanatory diagram of road surface image removal.

FIG. 19 is also an explanatory diagram of differential image creation.

FIG. 20 is an explanatory diagram of object edge detection similarly.

[Explanation of symbols]

1 Imaging unit 11R, 11L CCD camera 2 Rudder angle detector 3 storage 31R, 31L frame memory 35 Edge image memory 4 Data processing unit 41 CPU 42 ROM 43 RAM 5 Display 6 Voice instruction section 7 Image projection unit 100 vehicles 200 obstacles 300 white line (road image) 400 standard image

─────────────────────────────────────────────────── ─── Continuation of the front page (72) Inventor Naoto Ishikawa 1500, Onjuku, Susono-shi, Shizuoka Yazaki General Stock Company In-house (56) Reference JP-A-7-250319 (JP, A) JP-A-3-96451 (JP, A) JP-A-6-194580 (JP, A) (58) Fields investigated (Int.Cl. ⁷ , DB name) H04N 7/18 B60R 1/00 H04N 5/225

Claims (8)

(57) [Claims] 1. A vehicle periphery monitor for monitoring the periphery of a vehicle on the basis of image information from an image pickup means provided with a right side image pickup means and a left side image pickup means which are arranged at a predetermined position of the vehicle and are separated by a predetermined distance. In the apparatus, an image holding unit having a right side image holding unit holding the right side image information from the right side imaging unit and a left side image holding unit holding the left side image information from the left side imaging unit; and the right side image information or Magnification correction for enlarging / reducing the image information so that the size of the subject in the one image information and the size of the subject in the other image information are matched by enlarging / reducing at least one of the left image information. Means and the magnification correction means ensure that the sizes of the subjects match each other.
One of the image information is the back of all the images with height "0".
It is assumed that the image information is
One of the images captures the other of the image information.
The image information is recorded so that it becomes the image information captured at the image position.
Outputs the projection image information obtained by coordinate conversion of one of the
In addition to the image information in which the image information and the size of the subject match
Object extraction means for outputting the difference between the two as object information
And the edge in the image information held in the image holding means is detected.
The differential image that was output and the object information are overlaid and the AND is taken.
Image information that is output as object edge information.
A vehicle surroundings monitoring device characterized by recognizing an object existing around the vehicle from the edge detecting means and the object information and the object edge information. 2. The magnification correction means includes a target image determination means for determining image information to be a magnification conversion target based on image information from the right side imaging means or the left side imaging means, and a magnification conversion target by the target image determination means. The vehicle periphery monitoring device according to claim 1, further comprising a correction value acquisition unit that acquires a conversion magnification for the image information determined as above. 3. The target image determination means selects image information having a high imaging magnification as a magnification conversion target, and the correction value acquisition means reduces the image information selected as a magnification conversion target. The vehicle periphery monitoring device according to claim 2. 4. The correction value acquisition means obtains a correction value based on parallax information between a plurality of points of interest in the right side image information and a plurality of points of interest in left side image information corresponding to the points of interest in the right side image information. The vehicle periphery monitoring device according to claim 2 or 3, wherein the determination is made. 5. A reference image projecting means for projecting a reference image serving as a measurement reference in an image pickup area of the image pickup means is provided at an arbitrary position of a vehicle, and the magnification correction means sets the reference image to the right side image pickup means. The image information from the image pickup means is enlarged or reduced based on the left side reference image obtained by the left side image pickup means capturing the right side reference image and the reference image obtained by the image pickup by the left side image pickup means. Item 1, 2, 3 or 4
The vehicle periphery monitoring device described. 6. The right side image pickup means and the right side image pickup means based on image information from the right side image pickup means or the left side image pickup means.
Obtains the actual parallax of the image captured by the left image capturing means
Therefore, based on the installation parameters of the imaging means,
The difference between the parallax and the obtained actual parallax is referred to as parallax correction information.
A parallax correction unit that outputs the image information is output, and the object extraction unit corrects the projection image information based on the parallax correction information from the parallax correction unit. Alternatively, the vehicle periphery monitoring device according to item 5. 7. An object position calculating means for calculating the position of the object based on the image information held in the image holding means using the object edge detected by the object edge detecting means, the vehicle and the object. Display means for displaying the relative position of the object is provided, and the driver is informed of the relative position of the object and the vehicle based on the position information of the object output from the object position calculation means. The vehicle surroundings monitoring device according to Item 1, 2, 3, 4, 5 or 6. 8. An object position calculating means for calculating the position of the object based on the image information held in the image holding means using the object edge detected by the object edge detecting means, and the turning of the vehicle. A route prediction means for predicting the route of the vehicle based on the information, and an alarm means for issuing an alarm such as an alarm sound are provided, and the position information of the object output from the object position calculation means and the route prediction means are provided. 2. A collision is predicted between a vehicle and an object on the basis of predicted route information, and when a "collision" is predicted, an alarm is issued by at least one of the alarm means and the display means. The vehicle periphery monitoring device according to 2, 3, 4, 5, 6 or 7.