JP2003215434A - Range-finding device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a range-finding device capable of performing accurate range-finding at high speed by performing spatial frequency component extracting processing for detecting a phase difference only when the specified spatial frequency component must be extracted according to a subject condition. <P>SOLUTION: When a subject is the low-contrast one, filtering processing to extract the spatial frequency component being low frequency from subject image data is performed, and when the subject is the one in a counter light state, filtering processing to extract the spatial frequency component being high frequency from the subject image data is performed, whereby data in accordance with a subject distance is arithmetically operated. <P>COPYRIGHT: (C)2003,JPO

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a distance measuring device, and more particularly, to a distance measuring device used in a camera or the like for extracting a predetermined frequency component from subject image data and performing a distance measuring operation based on the extracted frequency component data. A distance device.

[0002]

2. Description of the Related Art Conventionally, in a passive range finder which performs a range finding calculation based on a phase difference between object images output from a pair of sensors, harmful frequency components included in object image data are removed and measured. In order to improve the distance accuracy, two different spatial frequency components are extracted from subject image data as disclosed in Japanese Patent Laid-Open No. 15223/1990, and two phase differences are obtained using the respective frequency component data. There is known a method in which the distance is detected, and one of the phase differences is selected to measure the distance.

[0003]

However, in the case of the method disclosed in Japanese Patent Application Laid-Open No. 2-15223, two spatial frequency components are always extracted, and the phase difference is detected for each frequency component. However, there is a problem in that the distance measurement time is increased.

An object of the present invention is to perform a high-speed and high-accuracy measurement by performing a frequency component extraction process for detecting a phase difference only when a predetermined spatial frequency component needs to be extracted depending on the subject condition. An object of the present invention is to provide a distance measuring device capable of performing distance.

[0005]

SUMMARY OF THE INVENTION A distance measuring device according to the present invention comprises a light receiving lens for forming a pair of object images on a pair of sensors, and an optical image of the pair of object images formed by the light receiving lens. A pair of sensors that convert into an electric signal according to the intensity, an integral control unit that controls the integral operation of the pair of sensors, a reading unit that reads the subject image data output from the pair of sensors, and the reading unit. In a distance measuring device comprising a calculation means for calculating data according to a subject distance based on the subject image data read by and a filter means for performing a filtering process for extracting a predetermined frequency component from the subject image data. ,
It is characterized in that whether or not to perform the filter processing is determined according to the subject condition, and when performing the filter processing, the frequency components to be extracted are switched.

Further, the subject condition is low contrast,
Alternatively, if the subject is backlit, filter processing is performed, low frequency components are extracted during low contrast, high frequency components are extracted during backlit, and the subject distance is determined based on the frequency components extracted from the subject image data. It is characterized in that the corresponding data is calculated.

When the difference between the maximum value and the minimum value of the subject image data is smaller than a predetermined value, it is determined that the contrast is low, the subject image data is divided into a plurality of areas, and the average brightness of each area is determined. A distance measuring device is used, which is characterized in that it is determined to be backlit when the difference between is larger than a predetermined value.

[0008]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 is a block diagram for explaining the outline of the first embodiment of the present invention. As shown in FIG.
a and 101b are line sensors 102a and 1b for the subject images.
It is a light receiving lens for forming an image on 02b. Also, 1
Reference numerals 02a and 102b denote line sensors that photoelectrically convert the subject image formed by the light receiving lenses 101a and 101b according to the light intensity of the subject image and convert it into an electric signal. And
An integration control circuit 103 controls the integration operation of the line sensors 102a and 102b. Further, 104 is a reading means for A / D converting an analog electric signal photoelectrically converted from the subject image, which is output from the line sensors 102a and 102b. A CPU 105 outputs various control signals and performs various calculations such as subject distance calculation. Further, 106 is a filter means for extracting a predetermined spatial frequency component from the subject image data read by the reading means 104.

In the distance measuring device having the structure as shown in FIG. 1, the brightness distribution of the object obtained by performing the integration control by the integration control means 103 is A / D converted by the reading means 104 and based on the object image data read out. Then, the subject for which the image data is acquired is a normal subject as shown in FIG.
It is determined whether the subject is a backlight subject as shown in FIG. 3 or a low contrast subject as shown in FIG.

Whether or not the subject is a low contrast subject is determined by, for example, the maximum value MAX of one of the data 114a of the subject image data output from the line sensors 102a and 102b as shown in FIG. It is performed by detecting the minimum value MIN and comparing the difference (MAX-MIN) with a predetermined determination value. If the difference is smaller than the determination value, it is determined to be a low contrast subject. The low-contrast determination is not limited to the above method, and may be a method such as using the sum of data change amounts at predetermined intervals for the determination. Note that the subject image data 114a of the main subject 113 in the shooting scene of the low-contrast subject in FIG. 7 is subject image data output from the line sensor 102a, and 114b is the line sensor 102.
This is the subject image data output from b. Also, MAX
Is the maximum value of the subject image data 114a, and MIN is the minimum value of the subject image data 114a.

Whether or not the subject is a backlit subject is determined, for example, in one of the subject image data output from the line sensors 102a and 102b in FIG. As shown in the figure, it is divided into a plurality of areas A, B, and C, the average value of the data in each area is calculated, and the difference between the average values is compared with a predetermined judgment value. If the difference is large, it is determined that the subject is a backlight subject. In the case of the subject image data 114a shown in FIG. 5, the difference between the average values of the area A and the area B is large, so it is determined that the subject is a backlight subject. The backlight judgment is not limited to the above method,
A method of making a determination based on the photometric data of the multi-division photometric sensor may be used.

When the subject is a normal subject such as the main subject shown in FIG. 2, as shown in FIG. 3, subject image data 1 output from the line sensors 102a and 102b.
Since 14a and 114b have sufficient contrast and the shapes of the two subject images are the same, the image data 114a and 114b are used as they are for the correlation calculation,
The phase difference (image shift amount) between the two subject images is obtained by interpolation calculation, and the subject distance is calculated from this phase difference.

If the subject is a low contrast subject, as shown in FIG. 8, the line sensors 102a and 102 are used.
subject image data 114a, 114b output from
Does not have sufficient contrast, so this image data 11
If 4a and 114b are used as they are, it is very difficult to obtain the correct subject distance. Therefore, in the equation (1), a = 5 is set, filter processing is performed to extract low-frequency spatial frequency components, and extracted data 115a and 115b are obtained as shown in FIG.
Using a and 115b, the phase difference (image shift amount) between the two subject images is obtained by correlation calculation and interpolation calculation, and the subject distance is calculated from this phase difference.

F (n) = S (n) −S (n + a) (1) (S (n) is the nth data of the subject image data) Further, 115b is the center of the subject image data 114a. It is the subject image data after extracting the low frequency spatial frequency component of the data of the region of the subject image data 114b corresponding to the B area of the part.

When the subject is a backlit subject, the line sensors 102a and 102a as shown in FIG. 5 are affected by, for example, ghosts and flares generated in the distance measuring optical system.
The shapes of the subject image data 114a and 114b output from the image b are not uniform, and the image data 114a and 114b are not uniform.
If is used as it is, it is very difficult to obtain the correct subject distance. Therefore, in the formula (1), a = 2
The extracted data 115 as shown in FIG. 6 is set by performing a filtering process for extracting high frequency spatial frequency components.
a, 115b are obtained, the phase difference (image shift amount) between the two subject images is obtained by correlation calculation and interpolation calculation using the data 115a, 115b, and the subject distance is calculated from this phase difference.

Further, the filter processing for extracting the predetermined spatial frequency component is not limited to the equation (1), but may be performed by a weighted average calculation or the like. Then, in the formula (1), F
(N) may have a negative value, and depending on the capability of the CPU 105, the calculation process may be troublesome. Therefore, in order to prevent this, as in equations (2) and (3), F A process in which (n) does not have a negative value may be used.

F (n) = | S (n) -S (n + a) | ... (2) F (n) = S (n) -S (n + a) + b ... (3) (b is Offset (Positive Value) As described above, according to the first embodiment, the frequency component extraction process for detecting the phase difference is performed only when the predetermined spatial frequency component needs to be extracted depending on the subject condition. In addition, it is possible to improve the distance measurement accuracy of a subject which is poor in low contrast, backlight, etc. without increasing the distance measurement time during the distance measurement of a normal subject.

Next, the correlation calculation will be described.

As shown in FIGS. 16 (a) and 16 (b), the line sensors 5a and 5b are composed of a plurality of photoelectric conversion elements, and sensor data a1, a2, ... AN, b1, b respectively.
2, ... bN is output. Data of a predetermined range (hereinafter, windows) 6a and 6b are extracted from this sensor data. As a method of extraction, the window 6a is fixed and the window 6b is
The simplest method is to shift each sensor by one sensor. The fixed side and the shift side may be reversed. The correlation amount F (n) is obtained by the equation (4) using the pair of extracted window data.

Reference numeral 5a in FIG. 16 is a line 5b sensor for photoelectrically converting the subject image formed by the light receiving lens according to its light intensity and converting it into an electric signal.
Is an extraction range (window) of the sensor data used for calculating the correlation amount.

[0022]

[Equation 1]

N is the shift amount, w is the number of data in the window, i is the data in window N0., K is the calculation area head sensor data N0, and the pair of windows 6a and 6b.
18 shows the highest degree of coincidence of data when F (n) obtained by shifting the window 6b by one sensor unit is a minimum value (F (n) = F _MIN ), as shown in FIG. Thus, the shift amount n = nF _MIN is the relative positional shift amount of the subject image. As a method of extracting a window, FIG.
As shown in (a) and (b), a method of alternately shifting the windows 6a and 6b may be used. In this case, the equation for obtaining the correlation amount F (na, nb) is as shown in equation (5).

Reference numeral 5a in FIG. 17 denotes a line 5b sensor for photoelectrically converting the subject image formed by the light receiving lens according to its light intensity and converting it into an electric signal.
Is an extraction range (window) of the sensor data used for calculating the correlation amount.

[0025]

[Equation 2] (Na is the shift amount of the window 6a, nb is the shift amount of the window 6b)

The relative positional deviation amount nF _MIN is F (n
sum of na and nb when (a, nb) is the minimum (na + n)
b).

Next, the interpolation calculation will be described.

Line sensors 5a, 5b obtained by correlation calculation
The relative positional deviation amount of the subject image formed on the upper side is shown in FIG.
According to the sensor pitch of the line sensor, as shown in FIG.
This is a discrete value, and this pitch width is the minimum resolution for ranging.
Become. Therefore, the distance can be measured only by the image shift amount obtained by the correlation calculation.
If this is done, the distance measurement accuracy will be coarse. There
Then, in order to improve the ranging accuracy, the discrete correlation amount F (n)
The following interpolation calculation is performed by using the above. Interpolation operation in general
Is a correlation amount F as shown in FIGS.
F which is the minimum value of (n)_MINAnd shift amount n before and after that
F_MIN-1, nF _MINCorrelation amount at +1
F_mnS, F_plSUsing_MINShift giving
Amount nF_MINAnd the true minimum F_MINRShift amount to give
nF_MINRThe deviation amount Δn from_mnS, F_plSof
Calculate according to equation (6) or equation (7) according to the size relationship
It is a thing.

When F _mnS > F _plS (FIG. _19A )

[Equation 3] When F _mnS ≤ F _plS (Fig. 19 (b))

[0030]

[Equation 4]

From the interpolation amount Δn obtained above, the true image shift amount nF _MINR is as _follows when F _mnS > F _plS (FIG. 19 (a)) n _FMINR = n _FMIN + Δn (8) F _mnS When ≦ F _plS (FIG. 19B), n _FMINR = n _FMIN −Δn (9).

Next, the procedure of the distance measuring sequence of the first embodiment will be described with reference to FIG.

As shown in FIG. 10, in S101, the sensitivities of the pair of line sensors 102a and 102b are set according to the subject brightness obtained by pre-integration or the like. S10
In 2, integration is performed with the sensor sensitivity set in S101. In S103, the pair of line sensors 102a, 10a
The subject image data output from 2b is A / D converted to C
It is stored in the memory area in the PU 105. In S104,
The maximum value MAX and the minimum value MIN of the subject image data read out in S103 are detected. In S105, the difference between the maximum value MAX and the minimum value MIN detected in S104 is compared with a predetermined low contrast determination value, and low contrast determination is performed. If MAX-MIN is larger than the judgment value, S106.
If it is smaller, proceed to S110. In S106, the average values of the subject image data between the backlight determination areas A, B, and C shown in FIG. 5 are compared, and the backlight determination is performed based on the maximum difference between the average values and a predetermined backlight determination value. Then, S107
Then, if the maximum value of the difference between the average values obtained in S106 is larger than the determination value, the process proceeds to S108, and if it is smaller, S109.
Proceed to. In S108, by the filter means 106,
Using the equation (1), the subject image data 114 shown in FIG.
Filter processing for extracting high-frequency spatial frequency components from a and 114b is performed. In step S109, the subject image data 114a, 114b or the subject image data after the filtering process is used to obtain the phase difference (image shift amount) between the two subject images by the correlation calculation and the interpolation calculation. Calculate the subject distance. Then, in S110, the filter means 106 performs a filtering process for extracting low frequency spatial frequency components from the subject image data 114a and 114b shown in FIG. 5 by using the expression (1).

Next, a second embodiment of the present invention will be described.

In the first embodiment, when it is determined that the subject is a backlight subject, a high-frequency spatial frequency component is extracted from the subject image data used for the backlight determination, and distance measurement is performed. On the other hand, in the second embodiment, in the case of backlighting, the object image data of the area that has lower luminance than the other areas in backlight determination, that is, area B in FIG. 4 is used as a reference. 14 and re-integrate to obtain subject image data 114a and 114b in which the contrast of the main subject is emphasized more than in FIG. 4 as shown in FIG. 14, and the data is subjected to a filtering process for extracting a high spatial frequency component. Extracted data 115 as shown in FIG.
By using a and 115b, the phase difference (image shift amount) between the two subject images is obtained by correlation calculation and interpolation calculation, and the subject distance is calculated from this phase difference.

As described above, according to the second embodiment of the present invention,
Since the contrast of the subject image data of the main subject becomes high, the distance measurement accuracy at the time of backlighting becomes even higher.

Next, the procedure of the distance measuring sequence of the second embodiment will be described with reference to FIG.

In S201, the pair of line sensors 102a, 1a, 1a, 1b, 1c, 1c, 1c, 1c, 1d, 1c, 1d, 1d, 1e, 1e, 1e, 2b, 2b, 2d, 1e, 2b, 2b, or 2d, depending on the subject brightness obtained by pre-integration or the like.
Set the sensitivity of 02b. In S202, integration is performed with the sensor sensitivity set in S201. In S203, the subject image data output from the pair of line sensors 102a and 102b is A / D converted and stored in the memory area in the CPU 105. In S204, the maximum value MAX and the minimum value MIN of the subject image data read in S203 are detected. In S205, the difference between the maximum value MAX and the minimum value MIN detected in S204 is compared with a predetermined low contrast determination value, and low contrast determination is performed. If MAX-MIN is larger than the determination value, the process proceeds to S206, and if it is smaller, S-MIN.
Proceed to 212.

Then, in S206, the average values of the object image data between the backlight determination areas A, B, and C shown in FIG. 4 are compared, and the backlight determination is performed based on the maximum difference between the average values and a predetermined backlight determination value. To do. In S207, if the maximum value of the difference between the average values obtained in S206 is larger than the determination value, S20
8. If it is smaller, proceed to S211. In S208,
In the backlight determination of S206, the re-integration is performed with reference to the subject image data of the area having the lower brightness than the other areas. In S209, the pair of line sensors 102a, 1a
The subject image data output from 02b is A / D converted and stored in the memory area in the CPU 105. In S210, the filter means 106 performs the filtering process for extracting the high-frequency spatial frequency component from the subject image data 114a and 114b shown in FIG. 4 by using the expression (1). S2
In 11, the subject image data 114a and 114b or the subject image data after the filter processing is used to obtain the phase difference (image shift amount) between the two subject images by correlation calculation and interpolation calculation, and from this phase difference, the subject distance is calculated. To calculate. S
In 212, the filter means 106 uses the formula (1) to calculate the subject image data 114a and 11 shown in FIG.
Filtering is performed to extract low frequency spatial frequency components from 4b.

As described above, according to the second embodiment of the present invention,
Compared with the first embodiment, more accurate distance measurement can be performed.

Next, a third embodiment of the present invention will be described.

In this embodiment, when it is determined that the subject is a backlit subject, the subject distance obtained by using the subject image data used for the backlight determination as it is and the low luminance compared to other areas in the backlight determination. 4, the object image data of area B in FIG. 4 is re-integrated, and as shown in FIG. 14, object image data 114a and 11a in which the contrast of the main object is emphasized more than in FIG.
4b, and subject data calculated using extracted data 115a and 115b as shown in FIG. 15 obtained by performing a filtering process on this data to extract a high-frequency spatial frequency component, whichever is more reliable. The object distance is selected. The reliability data S to be compared are the data F _mnS , F _plS , and F _min used in the interpolation calculation.
Is calculated by using the equation (10), and is calculated when each subject distance is calculated. This reliability data S indicates that the larger the value, the higher the reliability.

S = MAX (F _mnS , F _pls ) −F _min (10) (MAX (F _mnS , F _pls ): F _mnS , F _pls
The data of which the value of is larger) The reliability data used for selecting the subject distance is not limited to the one obtained by the equation (10), and may be obtained by using another method. By performing the above processing, for example, when flare, ghost, or the like does not occur at the time of backlighting, effective low frequency spatial frequency components are removed by the filter processing for extracting high frequency spatial frequency components. It is possible to prevent a side effect of the filter processing such as a decrease in distance measuring accuracy. According to the third embodiment, the distance measurement accuracy at the time of backlighting is further improved.

Next, the procedure of the distance measuring sequence of the third embodiment will be described with reference to FIG.

In S301, it is obtained by pre-integration or the like.
A pair of line sensors 102a, 1a depending on the brightness of the subject.
Set the sensitivity of 02b. In S302, set in S301
Integrate with the specified sensor sensitivity. In S303, a pair
Subject output from the line sensors 102a and 102b of
A / D conversion of body image data and memory area in CPU 105
Store in the area. In S304, the target read in S303 is read.
Detects maximum value MAX and minimum value MIN of image data
It In S305, the maximum value MAX detected in S304 and
The difference between the minimum value MIN and the predetermined low contrast judgment value
A comparison is made to make a low contrast determination. MAX-MIN
If it is larger than the judgment value, the process proceeds to S306, and if it is smaller than the judgment value, S
Proceed to 314. In S306, the subject image data 114
a and 114b, two by correlation calculation and interpolation calculation
The phase difference (image shift amount) of the subject image of
The subject distance is calculated from this. In addition, the data used during interpolation calculation
Data F _mnS, F_pls, F_minUsing (10)
The reliability data is obtained from the formula. In S307, FIG.
Of the subject image data between the backlight determination areas A, B, and C shown in
The average values are compared, and the maximum difference between the average values is
The backlight determination is performed based on the backlight determination value. In S308, S3
The maximum value of the difference of the average value obtained in 07 is larger than the judgment value.
If so, the process proceeds to S309, and if small, the process proceeds to S313. S
In 309, in the backlight determination of S307, other areas
Based on the subject image data of the area that was relatively low in brightness
And re-integrate. In S310, a pair of line sensors
Subject image data output from 102a and 102b is A
/ D-converted and stored in the memory area in the CPU 105.
In S311, the filter means 106 converts the equation (1) into
By using the subject image data 114a and 114b shown in FIG.
Filtering to extract high frequency spatial frequency components from
To do. In S312, the subject after the filtering process in S311
By using the body image data, two
Obtain the phase difference (image shift amount) of the subject image and from this phase difference
Calculate the subject distance. In addition, the data used during interpolation calculation
Ta F_mnS, F_pls, F_minUsing equation (10)
To obtain reliability data. In S313, S30
6. From the two object distances obtained in S312, S30
6, either of the reliability data obtained in S312
Choose one. In S314, the filter means 106 is used.
Then, using the equation (1), the subject image data shown in FIG.
The low frequency spatial frequency components from the filters 114a and 114b.
Filter out. In S315, in S314
Using the subject image data after filtering, correlation calculation,
The phase difference (image shift amount) between two subject images is calculated by interpolation calculation.
Then, the subject distance is calculated from this phase difference.

As described above, according to the third embodiment of the present invention,
Even in a low-contrast subject, a region having a relatively high contrast is detected, a filtering process for extracting a low-frequency spatial frequency component is performed, and distance measurement is performed. Therefore, distance measurement accuracy in low contrast is further improved. In each of the above-described embodiments, a pair of line sensors 102a are used as the light receiving element,
Although 102b is used, the same effect as each of the above-described embodiments can be obtained even with a configuration using a pair of area sensors 402a and 402b as shown in FIG. 13 and a configuration using a plurality of pairs of line sensors.

Reference numerals 401a and 401b in FIG. 13 denote a pair of light receiving lenses for coupling a subject, which will be described later, onto the pair of area sensors 402a and 402b.
Reference numeral 02b is a pair of area sensors for photoelectrically converting the subject image formed by the light receiving lenses 401a and 401b according to its light intensity.

403 is an area sensor 402a,
An integration control circuit for controlling the integration operation of 402b,
Reference numeral 404 denotes A / A which is an analog electric signal output from the area sensors 402a and 402b and obtained by photoelectrically converting a subject image.
It is a reading means for D conversion. Reference numeral 405 denotes a CPU that outputs various control signals and performs various calculations such as subject distance calculation. Reference numeral 406 denotes a filter unit that extracts a predetermined spatial frequency component from the subject image data read by the reading unit 404. Is.

According to the present invention, the following configurations are possible.

Appendix 1 A light receiving lens for forming a pair of object images on a pair of sensors, and a pair of sensors for converting the pair of object images formed by the light receiving lens into electric signals according to light intensity. Based on the subject image data read by the reading unit, the integration control unit for performing integration operation control of the pair of sensors, the reading unit for reading the subject image data output from the pair of sensors, A distance measuring device comprising a calculating means for calculating data according to a subject distance and a filter means for performing a filtering process for extracting a predetermined frequency component from the subject image data, and whether or not to perform the filtering process depending on the subject condition. A distance measuring device characterized by switching frequency components to be extracted when performing judgment and filtering.

Appendix 2 When the subject condition is low contrast or backlight, filter processing is performed, low frequency components are extracted when the contrast is low, and high frequency components are extracted when the backlight is high. The distance measuring device according to appendix 1, wherein data according to a subject distance is calculated based on the extracted frequency component.

Appendix 3 It is determined that the contrast is low when the difference between the maximum value and the minimum value of the subject image data is smaller than a predetermined value, the subject image data is divided into a plurality of areas, and the average brightness of each area is divided. The distance measuring device according to appendix 2, wherein it is determined that the light is a backlight when the difference between the two is larger than a predetermined value.

Supplementary Note 4 When the subject is backlit, reintegration is further performed with reference to the low luminance portion of the subject image data, and high frequency components are extracted from the subject image data obtained by the reintegration. 3. The distance measuring apparatus according to appendix 2, which is characterized by performing a filtering process.

Supplementary Note 5 The distance measuring device according to any one of supplementary notes 1 to 4, wherein the pair of sensors are line sensors or area sensors.

[0055]

As described above, according to the present invention,
Since the spatial frequency component extraction processing for detecting the phase difference is performed only when the extraction of the predetermined spatial frequency component is necessary according to the subject condition, the distance measuring device capable of performing high-speed and highly accurate distance measurement. Can be provided.

[Brief description of drawings]

FIG. 1 is a configuration diagram of a distance measuring device according to first to third embodiments according to an embodiment of the present invention.

FIG. 2 is a diagram showing a shooting scene of a normal subject and subject image data according to the embodiment of the present invention.

FIG. 3 is a diagram showing subject image data output from the line sensor according to the embodiment of the present invention.

FIG. 4 is a diagram showing a shooting scene of a backlight subject according to the embodiment of the present invention.

FIG. 5 is a diagram showing subject image data according to the embodiment of the present invention.

FIG. 6 is a diagram showing subject image data after a finoleta process for extracting a high-frequency spatial frequency component according to the embodiment of the present invention.

FIG. 7 is a diagram showing a shooting scene of a low-contrast subject according to the embodiment of the present invention.

FIG. 8 is a diagram showing subject image data according to the embodiment of the present invention.

FIG. 9 is a diagram showing subject image data after filter processing for extracting low frequency spatial frequency components according to the first embodiment of the present invention.

FIG. 10 is a flowchart showing a procedure of a distance measuring sequence according to the first embodiment of the present invention.

FIG. 11 is a flowchart showing a procedure of a distance measurement sequence according to the second embodiment of the present invention.

FIG. 12 is a flowchart showing a procedure of a distance measuring sequence according to a third embodiment of the present invention.

FIG. 13 is a diagram showing an example of a modification of the configuration of the distance measuring apparatus according to the embodiment of the present invention.

FIG. 14 is a diagram showing subject image data of a main subject by reintegration during backlighting according to the embodiment of the present invention.

FIG. 15 is a diagram showing subject image data after filter processing for extracting high-frequency spatial frequency components according to the embodiment of the present invention. .

FIG. 16 is a diagram showing a window shift method for correlation calculation according to the embodiment of the present invention.

FIG. 17 is a diagram illustrating another example of the window shift method of the correlation calculation according to the embodiment of the present invention.

FIG. 18 is a diagram showing a correlation data graph showing a correlation value for each shift value according to the embodiment of the present invention.

FIG. 19 is a diagram illustrating an interpolation calculation according to the embodiment of the present invention.

[Explanation of symbols]

5a. 5b ... Line sensor, 101a. 101b ... Light receiving lens, 102a. 102b ... Line sensor, 103 ...
Integral control means, 105 ... CPU, 106 ... Filter means, 112 ... Distance measuring field of view, 113 ... Main subject, 114
a. 114b ... Subject image data, 115a. 115b ...
Spatial frequency component 117a. 117b ... Extracted data

Claims (3)

[Claims] 1. A light-receiving lens for forming a pair of object images on a pair of sensors, and a pair of sensors for converting the pair of object images formed by the light-receiving lens into electric signals according to light intensity. An integral control means for performing integral operation control of the pair of sensors, a reading means for reading the subject image data output from the pair of sensors, and based on the subject image data read by the reading means, A distance measuring device comprising a calculating means for calculating data according to a subject distance and a filter means for performing a filtering process for extracting a predetermined frequency component from the subject image data. A distance measuring device characterized by switching frequency components to be extracted when performing judgment and filtering. 2. When the subject condition is low contrast or backlight, a filtering process is performed, a low frequency component is extracted when the contrast is low, and a high frequency component is extracted when the backlight is high. The distance measuring apparatus according to claim 1, wherein data corresponding to a subject distance is calculated based on the extracted frequency component. 3. When the difference between the maximum value and the minimum value of the subject image data is smaller than a predetermined value, it is determined that the contrast is low, the subject image data is divided into a plurality of areas, and the average brightness of each area is determined. The distance measuring device according to claim 2, wherein it is determined that the light is a backlight when the difference between the two is larger than a predetermined value.