JPH09119829A - Apparatus and method for measurement of distance - Google Patents

Abstract

PROBLEM TO BE SOLVED: To measure a distance at high speed by eliminating a bad influence due to a bias level difference by a method wherein sensor data which is constituted of a plurality of pixels is inverted by making use of a prescribed pixel position as an axis and the phase difference of a pixel position in which a symmetric peak obtained by an addition operation becomes a maximum value is detected. SOLUTION: A right-sensor-data intake part 4R and a left-sensor-data intake part 4L take into electric signals generated by optical sensors 3R, 3L as right and left sensor data. Inversion processing parts 5R, 5L perform an inversion processing operation regarding the right and left sensor data DR, DL. Adders 6R, 6L add the left sensor data DL to right sensor data DR'. A peak-value detection part 27 finds the peak value of the data DL+DR', and it finds a phase difference on the basis of the peak value. A measured-distance-value computing part 8 computes a measured distance value on the basis of the phase difference so as to be output.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to distance measuring, and more particularly to distance measuring technology using a triangular distance measuring method.

[0002]

2. Description of the Related Art FIG. 14A is a schematic view for explaining an external light triangular optical system of a phase difference detection type distance measuring device.
Light beams 134B, 1 emitted from the distance measurement object 133
34R passes through two lenses 131B and 131R,
It is projected on the two sets of optical sensors 132B and 132R.

Light beam 134 passing through reference lens 131B
B is imaged on the reference optical sensor 132B, and the image of the distance measurement object 133 is projected. The light beam 134R passing through the reference lens 131R is imaged on the reference light sensor 132R, and the image of the distance measurement object 133 is projected. The image of the distance measurement object 133 is projected on the reference light sensor 132B and the reference light sensor 132R, respectively.

If the distance measuring object 133 is located at infinity from the lens 131, the distance between the image formed on the standard light sensor 132B and the image formed on the reference light sensor 132R is the baseline length B. Becomes As shown in FIG.
Is separated from the lens 131 by a distance L, the image formed on the reference optical sensor 132B and the reference optical sensor 1
The distance between the images formed on 32R is B + x. That is, an image is formed on the optical sensor 132 with a distance of the phase difference x in addition to the baseline length B.

The distance f between the lens and the sensor is determined by the lens 131.
To the surface of the optical sensor 132 on which the optical image of the distance measurement object 133 is projected. The distance measuring distance L is the distance from the distance measuring object 133 to the lens 131, and this distance is measured as the distance from the distance measuring device to the distance measuring object.

As shown in the figure, it is assumed that the distance measuring object 133 is on the optical axis of the reference lens 131B. At this time, the optical axis of the reference lens 131R, the reference lens 1
The two triangles formed by the ray passing through the center of 31R, the object plane including the distance measurement object 133, and the image plane on the optical sensor 132 are similar, and the relationship of L / B = f / x (1) holds. .

That is, as shown in FIG. 14B, L = B · f / x (2) holds.

When x is represented by the number n of sensor pitches p, L = B · f / (n · p) (3)

The sensor pitch p is an interval between a plurality of light receiving elements forming an optical sensor, and takes a value of, for example, about 20 [μm]. At this time, the denominator is represented with an accuracy of an integral multiple of the sensor pitch p.

The sensor pitch p is further converted into k by using an interpolation method.
When it is divided and when x is represented by the subdivision, it corresponds to i, x = i (p / k), and L = B · f / (i / k) p (4) Become. In other words, the denominator can be represented by the interpolation method with an accuracy that is an integral multiple of p / k, and the distance measurement distance L that is more accurate than Expression (3) is obtained.

Next, the correlation calculation performed to obtain the phase difference x between the image on the standard light sensor 132B and the image on the reference light sensor 132R will be described. FIG. 15 is a conceptual diagram for explaining the phase difference detection by the correlation calculation.

FIG. 15A shows an image formed on the photosensor. The optical sensors 132B and 132R are line sensors in which a plurality of photodiodes are arranged one-dimensionally.
The number of photodiodes forming the photosensor 132 corresponds to the number of pixels of the image formed on the photosensor 132.
The number of pixels of the reference light sensor 132R is the standard light sensor 132R.
The number of pixels of B is equal to or more than that.

The reference optical sensor 132B includes a reference lens 1
An image of the object for distance measurement is formed via 31B. An image of the object to be measured is formed on the reference light sensor 132R separated from the reference light sensor 132B in the horizontal direction of the base line via the reference lens 131R.

When the object to be measured is at the infinity position, the same image is formed on the light receiving elements of the photodiodes corresponding to the standard light sensor 132B and the reference light sensor 132R. If the object to be measured is not at infinity, the optical sensor 13
The images on 2B and 132R are displaced in the horizontal direction. That is, the distance between the images increases as the object to be measured approaches, and the distance between the images decreases as the object to measure distance increases. In order to detect the variation in the distance between the images, the reference light sensor 132R
In many cases, the number of pixels is set to be larger than that of the reference light sensor 132B.

In order to detect the variation in the distance between the image on the standard light sensor 132B and the image on the reference light sensor 132R, a phase difference detection method by a correlation calculation is used. In the phase difference detection by the correlation calculation, the correlation value H (n) of the pair of image formations on the optical sensors 132B and 132R is obtained by the calculation based on the following equation (5), and these image formations are performed until the correlation value becomes the minimum. The relative movement value (phase difference) of is calculated.

H (n) = Σ (j = 1 to i) | B (j) −R (j + n) | (5) where Σ (j = 1 to i) is from j to 1 Represents the sum of functions. j designates a pixel in the reference light sensor 132B. Further, n is an integer from -6 to 6, for example, and indicates the relative movement amount in the reference light sensor.

B (j) is an electrical signal output from each pixel of the reference photosensor 132B in time series, and R (j +
n) is an electric signal output from the pixel of the reference light sensor 132R in time series.

FIG. 15B shows the relationship between the pixel shift amount and the correlation value. When the calculation of the above equation (5) is performed every time the pixel shift amount n is sequentially changed from −6 to 6, correlation values H (−6), H (−5), ..., H as shown in FIG. (6) is obtained. For example, it is set in advance so that the distance to the object to be measured becomes a predetermined value when the correlation value H (0) becomes the minimum value. When the correlation value at the position deviated from this is the minimum value, the deviation of the object to be measured from the predetermined position, that is, the distance to the object to be measured can be detected by the amount of deviation.

By the way, the light receiving elements of the standard light sensor 132B and the reference light sensor 132R are arranged at a pitch of 20 [μm], for example. The correlation value is 20 on the image plane.
It is calculated for each distance in units of [μm]. When the distance to the object to be measured corresponds to the middle position of the pitch of the light receiving element, make sure that the correlation value on the right side of the extreme value of the correlation value and the correlation value on the left side are different as shown by the broken line in the figure. Become. In such a case, it is possible to obtain a resolution equal to or greater than the pitch interval by performing interpolation calculation.

FIG. 15C is a schematic diagram for explaining the method of three-point interpolation. The position where the minimum correlation value is obtained is defined as x2, and the sample positions on both sides thereof are defined as x1 and x3. The correlation value actually obtained by calculation is shown by a black circle. As shown in the figure, when the correlation value y3 at x3 is lower than the correlation value y1 at x1, it is considered that the true minimum value exists somewhere in advance from x2 to x3.

If the minimum value is exactly at the position of x2, the correlation value curve is bent at x2 as shown by the broken line g1, and if it rises symmetrically, the correlation value y3a at x3 is the correlation value y1 at x1. Will be equal.

On the other hand, if the midpoint of x2 and x3 is the position of the true minimum correlation value, the correlation value curve is bent at the midpoint of x2 and x3 as shown by the broken line g2, and the correlation value y2 at x2 becomes The correlation value y3b at x3 becomes equal. As shown in the figure, the difference (y
3a-y3b) is the difference in correlation value between x1 and x2 (y1-
equal to y2). That is, the correlation value of one unit changes as the pitch advances by half a pitch. Therefore, the true correlation value minimum position can be obtained by checking which intermediate position of the above-mentioned two cases the correlation value actually obtained by the calculation is. The shift amount d from x2 is given by d = (y1-y3) / 2 (y1-y2) (6) when the distance between adjacent sample points is 1.

[0023]

At present, a distance measuring device having a large number of pixels is desired. For example, there is a distance measuring device having a two-dimensional pixel area. Two-dimensional distance measuring device is 2
It is possible to detect distance measurement values for a plurality of areas within the dimensional area. As shown in Expression (5), the correlation calculation used for distance measurement requires more calculation as the number of pixels increases, and thus it takes a long time to obtain the distance measurement value.

Further, an amplifier and an A / D connected to the sensor
When the converter is provided separately for the standard sensor and the reference sensor, the sensor data from the two sensors will have different bias levels. If the bias level is different, the correlation calculation is adversely affected.

An object of the present invention is to provide a distance measuring device which eliminates the adverse effect of a bias level difference and can perform distance measurement at high speed.

[0026]

A distance measuring apparatus according to the present invention includes a data input terminal for receiving first and second sensor data output from first and second photosensors each composed of a plurality of pixels. For the second sensor data,
Inversion adding means for generating inverted sensor data which is inverted around a predetermined pixel position and adding the first sensor data and the inverted sensor data of the second optical sensor to generate a symmetrical peak, and a symmetrical peak Detects the maximum pixel position,
Peak value detecting means for detecting a phase difference between the image on the first optical sensor and the image on the second optical sensor, and measuring for calculating a distance measuring value according to the phase difference detected by the peak value detecting means. Distance value calculating means.

Since the symmetrical peak is generated and the distance measurement value is obtained, even if there is a bias level difference between the sensor data obtained by the first optical sensor and the sensor data obtained by the second optical sensor, the difference is canceled. be able to.

Further, by detecting the pixel position where the symmetrical peak has the maximum value and detecting the phase difference, the amount of calculation is smaller and the operation speed is higher than in the case where the correlation calculation of the sensor data is performed and the phase difference is detected. It is possible to measure various distances.

[0029]

1 is a view for explaining the function of a distance measuring device according to a first embodiment of the present invention.

The sensor unit is the right sensor unit 1R.
And the left sensor unit 1L. Right sensor unit 1
R has a right lens 2R and a two-dimensional optical sensor 3R.
The left sensor unit 1L has a left lens 2L and a two-dimensional optical sensor 3L. The optical sensors 3R and 3L convert the amount of light incident through the lenses 2R and 2L into electric signals.

The right sensor data fetching section 4R fetches the electric signal generated by the optical sensor 3R as right sensor data. The left sensor data capturing unit 4L captures the electric signal generated by the optical sensor 3L as left sensor data.

FIG. 2 shows a specific example of sensor data. The horizontal axis is the pixel position, and the vertical axis is the sensor data. Although the sensor data is two-dimensional data, since the processing is performed for each line data, the line data will be described below.

DR is the right sensor data captured by the right sensor data capturing section 4R. DL is the left sensor data captured by the left sensor data capturing unit 4L. Right sensor data DR and left sensor data D
The shift amount (phase difference) of L is d. The data a1 generated by the right sensor is shifted by d in the left sensor,
Taken in as 2.

In FIG. 1, the right sensor data inversion processing section 5R inverts the right sensor data DR.
The left sensor data inversion processing unit 5L uses the left sensor data DL
Inversion processing is performed for.

The inversion processing units 5R and 5L perform processing line by line. The sensor data inverted with respect to the pixel position is generated with a certain position (for example, the middle) in one line as an axis.

FIG. 3 shows a specific example of the inverted sensor data. DR ′ is inverted sensor data obtained by inverting the right sensor data DR (FIG. 2) on the axis A. Sensor data D
The data a1 located on the left of the axis A in R is located on the right of the axis A as the data a1 ′ in the sensor data DR ′.

DL 'is inverted sensor data obtained by inverting the left sensor data DL (FIG. 2) along the axis A. Data a2 located to the right of axis A in sensor data DL
Is located on the left of the axis A as the data a2 ′ in the sensor data DL ′.

The shift amount between the inverted sensor data DR 'and DL' is d. However, since the sensor data is inverted, the shift direction is opposite to that in the case of the sensor data DR and DL (FIG. 2).

In FIG. 1, the adder 6R adds the left sensor data DL and the right inverted sensor data DR '. The adder 6L has the right sensor data DR and the left inverted sensor data D.
Add L '.

In FIG. 4, sensor data DR + DL 'and sensor data DL + D, which are the addition results of the adders 6R and 6L, are shown.
An example of R'is shown. The sensor data DR + DL ′ is data obtained by adding the data DR (FIG. 2) and the data DL ′ (FIG. 3). The sensor data DL + DR ′ is data obtained by adding the data DL (FIG. 2) and the data DR ′ (FIG. 3).

Data c1 in the sensor data DR + DL '
Is an added value of the data a1 (FIG. 2) and the data a2 ′ (FIG. 3). Data c2 in the sensor data DL + DR '
Is an added value of the data a2 (FIG. 2) and the data a1 ′ (FIG. 3).

The amount of deviation between the sensor data DR + DL 'and the sensor data DL + DR' is d. In FIG. 1, the correlation calculation unit 7 performs the correlation calculation between the sensor data DR + DL ′ and the sensor data DL + DR ′ using the equation (5). The correlation calculation does not need to be performed on all sensor data. In FIG. 4, only the sensor data on the left of the axis A needs to be performed. If the axis A is located at the center of all the sensors, half the amount of correlation calculation is required. The correlation calculation may be performed only on the sensor data on the right side of the axis A.

The sensor data DR + DL 'and the sensor data DL + DR' each include all sensor information in the left area with the axis A as a boundary. Also for the right area,
Contains all sensor information. Therefore, it is sufficient to perform the correlation calculation on either the right or left region without performing the correlation calculation on all the regions.

Further, since the sensor data DR + DL 'and the sensor data DL + DR' are both data obtained by adding the information of the right sensor and the information of the left sensor, they have the same bias level. For example, assuming that the bias level of the right sensor is r1 and the bias level of the left sensor is r2, the right sensor data and the left sensor data are respectively expressed by DR (n) + r1 DL (n) + r2. Here, n is a pixel position.

The right inverted sensor data and the left inverted sensor data are represented by DR (n) '+ r1 DL (n)' + r2, respectively.

The data added by the adders 6R and 6L is
Each is represented by DL (n) + DR (n) ′ + r1 + r2 DR (n) + DL (n) ′ + r1 + r2. In both cases, the bias level is r1 + r2. The bias level is canceled by performing the correlation calculation on these two data.

In FIG. 1, the correlation calculation unit 7 uses the equation (5)
After performing the correlation calculation of, the three-point interpolation calculation of Expression (6) is performed to obtain the minimum correlation value. The distance measurement value calculation unit 8 calculates the distance measurement value L by the formula (4) based on the obtained minimum correlation value.
And output.

FIG. 5 is a model in which the data of the above-described calculation process is simplified. The right data DR has pixel data α1 and pixel data α2. The left data DL has pixel data β1 and pixel data β2. The same object is represented as data α1, α2 on the right sensor and data β1, β2 on the left sensor. The shift amount (phase difference) between the right data α1 and α2 and the left data β1 and β2 is d.

The right inverted data DR 'is data obtained by inverting the right data DR on the axis A. The left inverted data DL ′ is data obtained by inverting the left data DL on the axis A. Right data α
The phase difference between 1 and α2 and the left data β1 and β2 is still d.

The data DR + DL 'is data obtained by adding the right data DR and the left inverted data DL'. Data DL
+ DR ′ is data obtained by adding the left data DL and the right inverted data DR ′. Data DR + D with axis A as the boundary
The area on the left side of L'includes data α1 and β2. In the area on the left side of the data DL + DR ′, the data β1,
α2 is included.

That is, if the correlation value between the area on the left side of the data DR + DL 'and the area on the left side of the data DL + DR' is calculated, all the data α1, α2, β1, β2.
Will be reflected. The phase difference at this time is d.

If the correlation calculation is performed on the left side area, it is not always necessary to perform the correlation calculation on the right side area.
It should be noted that the data DR + DL ′ and the data DL + DR ′ on the right-hand side of the respective areas also have all the data α1, α.
Since 2, β1 and β2 are included, the correlation calculation may be performed only for the right area.

Next, the principle of addition of sensor data will be described. As shown in FIGS. 15A to 15C, the correct phase difference d can be obtained by performing the correlation calculation between the right sensor data DR and the left sensor data DL. In the present embodiment, instead of this, it is shown that the correlation calculation between the data DR + DL ′ and the data DL + DR ′ is performed. It will be described that the correct phase difference d can be obtained even in this case. That is, the phase difference d is stored even between the data DR + DL ′ and DL + DR ′ obtained by adding the sensor data.

FIG. 6 shows general basic functions f (x), f
(X-d), g (x), g (x-d) are shown. Function f
(X) and the function g (x) are independent of each other. Function f
(X-d) is a function deviated from the function f (x) by d. The function g (x-d) is d with respect to the function g (x).
It is a function that is deviated.

Here, the function f (x) corresponds to the data DR, and the function f (x-d) corresponds to the data DL. Function g
(X) corresponds to the data DL ′, and the function g (x−d) corresponds to the data DR ′.

FIG. 7 shows a function H obtained by adding basic functions.
(X) and H (x-d) are shown. When the function H (x) is represented by H (x) = f (x) + g (x), the function H (x-d) is H (x-d) = f (x-d) + g (x- d) can be represented.

At this time, the function H (x) and the function H (x-d)
It is proved that the phase difference d is also preserved between and. Therefore, even if the correlation calculation is performed between the function H (x) and the function H (x-d), the correct phase difference d can be detected.

From the above, data DR + DL 'and data D
Even when the correlation calculation is performed between L + DR ′, the correct phase difference d can be detected. The data DR + D
Since sensor data of objects having different distances are added to L ′ and DL + DR ′, there is a problem in that respect.

However, originally, the two-dimensional image projected on the sensor is a mixture of objects in perspective and perspective, and the mixture of perspective is approved from the beginning. Therefore, regarding the sensor data, no special problem occurs even if data with different distance information is added.

FIG. 8 shows the overall structure of the distance measuring device according to this embodiment. The sensor unit includes a right sensor unit 1R and a left sensor unit 1L. Right sensor unit 1R
Has a right lens 2R and a two-dimensional optical sensor 3R, and the left sensor unit 1L has a left lens 2L and a two-dimensional optical sensor 3L. The optical sensors 3R and 3L convert the amount of light incident through the lenses 2R and 2L into electric signals.

The system controller 14 is, for example, a microcomputer, receives a timing pulse generated by the sensor control system 12, and returns a sensor control signal to the sensor control system 12. The sensor control system 12 supplies a drive pulse to the drive circuits 11R and 11L based on the sensor control signal.

The drive circuits 11R and 11L drive the sensors 3R and 3L according to the drive pulse. Sensor 3R, 3
The sensor data is supplied from L to the sensor data quantization unit 13. The sensor data quantizer 13 quantizes sensor data.

The system controller 14 supplies the write control signal and the write address to the image memory 15. The image memory 15 is, for example, an SRAM, and stores the quantized data quantized by the sensor data quantization unit 13 according to the write control signal.

The arithmetic unit 16 is, for example, a RISC microcomputer, and sends a transfer control signal to a parallel input / output circuit (parallel I
O) supply to 18. The parallel input / output circuit 18 takes in conditions such as an area for which distance measurement is desired from an external device 19 and transfers it to the data transfer memory 17. The data transfer memory 17 is, for example, SRAM.

The arithmetic unit 16 also supplies the read / write control signal and the address to the image memory 15 or the data transfer memory 17. The calculation unit 16 reads the sensor data DR, DL from the image memory 15, performs an inversion process on the sensor data, and generates inverted data DR ′, DL ′.

After that, addition processing is performed and data DR + D
L ′, DL + DR ′ are generated, and the correlation calculation between the data DR + DL ′ and the data DL + DR ′ is performed. After the correlation calculation, three-point interpolation is performed to obtain a highly accurate phase difference d.
After obtaining the phase difference d, the distance measurement value is calculated.

The arithmetic section 16 writes the obtained distance measurement value in the data transfer memory 17. The parallel input / output circuit 18 is
Upon receiving a transfer control signal from the arithmetic unit 16, the distance measurement value stored in the data transfer memory 17 is transferred to the external device 19.

FIG. 9 is a flow chart showing the processing procedure of the distance measuring apparatus according to this embodiment. The distance measuring device can detect the distance measuring value in each area in a plurality of areas in the two-dimensional area.

In step S1, the sensor data obtained from the optical sensors 3R and 3L is written in the image memory 15 as two-dimensional image data. The system controller 14 performs the process of step S1. The calculation unit 16 performs the subsequent processing.

In step S2, various conditions obtained from the external device 19 are loaded into the data transfer memory 17. The various conditions include, for example, designation of an area for which distance measurement is desired and designation of the size of the area, and are used when performing a distance measurement value calculation later.

In step S3, it is determined whether or not the processing of all lines has been completed. The two-dimensional image data consists of a plurality of lines, and processing is performed for each line. If the arithmetic processing has not been completed for all lines, the process proceeds to step S4.

In step S4, the image memory 15
Capture line data. In step S5, preprocessing of the captured line data is performed. This pretreatment is an important treatment in this embodiment.

The calculation section 16 performs inversion processing on the sensor data DR, DL fetched from the image memory 15 to generate inverted data DR ', DL'. After that, addition processing is performed to generate data DR + DL ′ and DL + DR ′.

In step S6, it is determined whether or not the processing for all areas has been completed. The line data includes a plurality of areas. When the arithmetic processing is not performed for all areas in the line data, the process proceeds to step S7.

In step S7, the correlation calculation for one area is performed. Correlation calculation is performed by data DR + DL ′ and data DL +
Perform during DR '. After that, three-point interpolation according to the equation (6) is performed to obtain a highly accurate phase difference d. Then, the distance calculation is performed using the equation (4) to obtain the distance measurement value.

In step S8, the data of the obtained distance measurement value is written in the transfer memory 17. After that, the process returns to step S6 to obtain the distance measurement value for the next area. When it is determined in step S6 that the calculation has been completed for all areas in the line data, step S3
Return to and repeat the process for the next line.

If it is determined in step S3 that the calculation has been completed for all lines, the process is ended. FIG. 10 is a diagram for explaining the function of the distance measuring device according to the second embodiment of the present invention.

The sensor units 1R and 1L, the sensor data fetching units 4R and 4L, the sensor data inversion processing unit 5R,
5L and adders 6R and 6L are the same as in the first embodiment (FIG. 1). The adder 6R outputs data DL + DR ', and the adder 6L outputs data DR + DL'.

The peak value detector 27 uses the data DL + D
Find the peak value of R '. Then, the phase difference d is obtained based on this peak value. That is, the peak value is detected instead of the correlation calculation, and the phase difference d is obtained. Details will be described later. Note that the peak value of the data DR + DL ′ may be obtained instead of the data DL + DR ′.

The distance measurement value calculation unit 8 calculates and outputs the distance measurement value based on the phase difference d. FIG. 11 is a graph showing a method of detecting the phase difference d by the peak value detecting unit 27 of FIG.

The horizontal axis is the pixel position n, and the vertical axis is the function P.
(N). The function P (n) is P (n) = DL (n) + DR (n) 'and indicates the output value of the adder 6R.

The axis A is for the sensor data inversion processing units 5R and 5R.
This is the axis when the sensor data is inverted at L.
The axis B is an axis representing the peak value of the function P (n). Axis A
The position of is known. The position of the axis B is a parameter to be obtained by peak detection.

The function P (n) is substantially symmetrical about the axis B. The vicinity of the axis B forms a convex portion. The distance between the axis A and the axis B is d / 2, which is half the phase difference d. This is clear even if FIG. 4 and FIG. 5 are seen.

Since the position of the axis A is known, the phase difference d can be obtained if only the position of the axis B can be detected.
If the phase difference d is obtained, the distance measurement value can be obtained. Next, a method of detecting the position of the axis B, that is, the peak value of the function P (n) will be described.

FIG. 12 is a graph showing a method for detecting the peak value of the function P (n). The horizontal axis represents the pixel position n, and the vertical axis represents the function S (n). The function S (n) is S (n) = P (n) -P (n + k) ... (7). The graph in the figure shows the case where k is 2.

The pixel position n (horizontal axis) of the axis A is known in advance. The pixel position where the function S (n) becomes 0 is ZR.
The distance between the axis A and the zero point ZR is d / 2 + k / 2. The zero point ZR corresponds to the position of the axis B.

Therefore, the phase difference d can be obtained by detecting the zero point ZR. By this method, if the phase difference d is obtained, it is not necessary to perform the correlation calculation, and the calculation time is considerably shortened. The distance measurement value can be obtained at high speed. Also, the function P (n) = DL (n) + DR
Since it is based on (n) ', as described above, it is not adversely affected by the bias level difference between the left and right sensors.

In this embodiment, k in equation (7)
However, k may be another value. It is desirable to reduce the value of k when the peak of the function P (n) has a sharp convex portion, and to increase the value of k when the peak has a gentle convex portion including a flat portion. Therefore, as a preprocessing, the value of k may be determined after examining the shape of the convex portion.

Further, not only when the phase difference d is detected using the function S (n) of the equation (7), but also by another method, the position of the axis B showing the peak in FIG. The phase difference d may be detected.

A symmetric function P (n) = D for peak detection
When L (n) + DR (n) ′ is generated, sensor data DR is generally set with the pixel position in the center of the sensor as an axis.
It is preferable to invert (n) and generate inverted data DR ′ (n).

However, when the sensor data DR (n) has a high frequency, the correct phase difference d may not be detected depending on the position of the axis. Next, a coping method in that case will be described. FIG. 13 is a graph showing a method of obtaining the phase difference d based on the high frequency sensor data DR and DL. The horizontal axis is the pixel position, and the vertical axis is the sensor data.

Right sensor data DR and left sensor data DL
The phase difference of is d. The peak data a1 generated by the right sensor is deviated by d in the left sensor and is represented as a2.

Axis C shows the pixel position in the middle of the sensor. Both the sensor data DR and DL have peaks a1 and a2 to the left of the axis C. In this case, even if the inverted data is generated based on the axis C and the data DR + DL ′ is obtained, two peaks are formed and the correct phase difference d cannot be obtained.

Therefore, the axis A is set at the pixel position between the peak a1 and the peak a2, and the inverted data DR 'and DL' are generated. The right inverted data DR ′ is data obtained by inverting the right sensor data DR on the axis A. The peak data a1 of the sensor data DR is represented as data a1 ′ in the sensor data DR ′.

The left inverted data DL 'is the left sensor data D.
It is data obtained by inverting L on the axis A. The peak data a2 of the sensor data DL is represented as data a2 'in the sensor data DL'. The phase difference between the inverted sensor data DR 'and DL' is d.

The sensor data DR + DL 'is the right data D
This is data obtained by adding R and the left inverted data DL ′. The sensor data DL + DR ′ is data obtained by adding the left data DL and the right inverted data DR ′.

Peak detection may be performed on either data DR + DL 'or data DL + DR'. Assuming that the pixel position of the peak detected by peak detection is axis B, the interval between axis B and inversion axis A is represented by d / 2.

As described above, by detecting the peak value of the data DR and the peak value of the data DL and determining the position of the axis A according to the pixel position corresponding to the peak value, the correct phase difference d is detected. can do.

Thus, when one of the two sensor data is inverted and added to the other, the corresponding peaks overlap,
High frequency data can be handled by selecting the inversion axis so as to form one peak. For example, choose an inversion axis within the shift range of the corresponding peak.

Further, by defocusing the optical system, the wavelength (pixel number) of the sensor data may not exceed the maximum shift number that can be detected. In other words, the sensor data may be converted into low frequency.

According to the second embodiment, there is no adverse effect due to the bias level difference between the left and right sensor data. In addition, instead of the correlation calculation, peak detection is performed and the phase difference d is detected, so that the calculation time can be considerably shortened and high-speed distance measurement can be performed.

The distance measuring device according to this embodiment can be used for both a general camera and a vehicle. If it is used for vehicles, it can perform multi-point distance measurement at high speed, which is a great advantage.

The present invention has been described in connection with the preferred embodiments.
The present invention is not limited to these. For example, it will be apparent to those skilled in the art that various modifications, improvements, combinations, and the like can be made.

[0104]

As described above, according to the present invention,
Even if there is a bias level difference between the sensor data obtained by the first optical sensor and the sensor data obtained by the second optical sensor, a symmetrical peak is generated and the distance measurement value is obtained, so that the difference can be canceled. .

Further, by detecting the pixel position where the symmetric peak has the maximum value and detecting the phase difference, the amount of calculation is smaller than that in the case where the correlation calculation of the sensor data is performed and the phase difference is detected. It is possible to measure various distances.

[Brief description of the drawings]

FIG. 1 is a block diagram for explaining a function of a distance measuring device according to a first embodiment of the present invention.

FIG. 2 is a graph showing a specific example of sensor data DR and DL.

FIG. 3 is a graph showing a specific example of inverted sensor data DR ′ and DL ′.

FIG. 4 is an addition sensor data DR + DL ′, DL + DR ′.
It is a graph which shows the example of.

FIG. 5 is a schematic diagram in which data in the calculation process of the present embodiment is simplified.

FIG. 6 shows general basic functions f (x), f (x-d), g
It is a graph which shows (x) and g (x-d).

FIG. 7 shows functions H (x) and H (x−, which are obtained by adding basic functions.
It is a graph which shows d).

FIG. 8 is a block diagram showing an overall configuration of a distance measuring device according to the present embodiment.

FIG. 9 is a flowchart showing a processing procedure of the distance measuring apparatus according to the present embodiment.

FIG. 10 is a block diagram for explaining the function of the distance measuring device according to the second embodiment of the present invention.

FIG. 11 is a graph showing a method of detecting a phase difference by the peak value detection unit of FIG.

FIG. 12 is a graph showing a method for detecting a peak value of a function P (n).

FIG. 13 is a graph showing a method for obtaining a phase difference based on high-frequency sensor data.

FIG. 14 is a schematic diagram for explaining a measuring method of a distance measuring distance. FIG. 14A is a schematic diagram of an external light triangulation optical system of the phase difference detection type distance measuring device, and FIG. 14B is an arithmetic expression for calculating the distance measuring distance.

FIG. 15 is a diagram for explaining phase difference detection by correlation calculation. FIG. 15A is a graph showing image signals obtained in the reference part and the reference part, FIG. 15B is a graph showing obtained correlation value curves, and FIG. 15C is for explaining a three-point interpolation method. FIG.

[Explanation of symbols]

 1 Sensor Unit 2 Lens 3 Optical Sensor 4 Sensor Data Importer 5 Sensor Data Inversion Processor 6 Adder 7 Correlation Calculator 8 Distance Measurement Calculator 11 Drive Circuit 12 Sensor Control System 13 Sensor Data Quantizer 14 System Controller 15 Image Memory 16 Calculation unit 17 Data transfer memory 18 Parallel input / output circuit 19 External device 27 Peak value detection unit

Claims (2)

[Claims] 1. A data input terminal for receiving first and second sensor data output from first and second photosensors each having a plurality of pixels, and a predetermined pixel position for the second sensor data. Inverting and adding means (5R, 5R, which generates inverted symmetrical sensor data by inverting with respect to the axis, and adds the first sensor data and the inverted sensor data of the second optical sensor to generate a symmetrical peak.
6R), and a peak value detecting means (27) for detecting a pixel position where the symmetrical peak has a maximum value and detecting a phase difference between the image on the first photosensor and the image on the second photosensor. And a distance measuring value calculating means (8) for calculating a distance measuring value according to the phase difference detected by the peak value detecting means. 2. A step of receiving first and second sensor data output from first and second photosensors each composed of a plurality of pixels, and an axis of a predetermined pixel position for the second sensor data. Generating inverted sensor data that has been inverted and then adding the first sensor data and the inverted sensor data of the second photosensor to generate a symmetrical peak; and a pixel in which the symmetrical peak has a maximum value. A step of detecting the position and detecting a phase difference between the image on the first optical sensor and the image on the second optical sensor; and calculating a distance measurement value according to the phase difference detected by the peak detection. A distance measuring method including a process.