JPS59155807A - Automatic focus detecting device - Google Patents

Abstract

PURPOSE:To raise remarkably a detecting accuracy and a detecting speed by executing a correlating operation by using only a part of a picture data obtained by an image sensor, and also executing the correlating operation by using a data shifted by plural pieces each of the picture data in case the defocus quantity is large. CONSTITUTION:A titled device is provided with a light shielding plate 7 having an opening 7a provided in the vicinity of a pupil on the front side of an image forming lens 6, and at the time of focusing, an image Q is formed on an image surface 8, and at the time of non-focusing, out-of-focus images Q1, Q2 are formed on the image surface 8 at a position shifted in the reflecting direction in the direction vertical to each optical axis O with regard ro the image Q in accordance with front-focusing and rear- focusing. Also, when the opening 7a of the light shielding plate 7 is moved to the opposide side against the optical axis O, an image Q' is formed on the image surface 8 at the time of focusing, and out-of-focus images Q1', Q2' are formed on the image surface in accordance with front-focusing/rear-focusing at the time of non-focusing. Accordingly, when a position of the light shielding plate is moved downward from upward against the optical axis, a state of the image in a state of focusing, front-focusing and rear-focusing is measured by an image sensor provided on the image surface 8.

Description

DETAILED DESCRIPTION OF THE INVENTION The present invention is an automatic focus detection device used in optical systems such as microscopes and cameras. The present invention relates to an automatic focus detection device that performs focus detection by individually converting each image into a photoelectric output signal using a conversion device and detecting the relative positional relationship between two images based on the photoelectric output signal.

Conventional automatic focus detection devices of this type include a rangefinder type that uses triangulation and a TTL type that divides the light flux passing through the pupil to obtain two images. For detection, the correlation between the two images was calculated digitally, and the extreme value of the correlation value was taken as a match, and the amount of relative movement of the two images until the match was taken as the amount of phase difference between the images. .

Figure 1 shows an example of this, in which data A and B of two images taken by an image sensor (not shown) are passed through a sample hold circuit, an A-D converter (both not shown), etc. The signals are stored in shift registers 1a and 1b, respectively. In this example, the image data is composed of 128 bits.

Both image data A and B are sent to shift registers la.

1b, then the circuit 2 that calculates the absolute value of the difference
The absolute value of the difference for each bit is determined by υ, and the sum of these is determined by the adder 3 to obtain a correlation value between the two images. Next, the image data B in the shift register 1b is shifted by one pit by a pulse from the clock OL, and the image data B in the shift register 1b is shifted again to the circuit 2. Adder 3 calculates the correlation value. In this way, a correlation value is determined each time one image data is moved one after another by the clock OL, and the peak detector 4 further determines the extreme value of the correlation value, and the position where the extreme value is detected is determined as the in-focus position. Become. Further, the number of clocks in the case of the extreme value is determined by the counter 5, and the number of clocks, that is, the amount of movement of the image data B in the shift register 1b becomes the amount of phase difference between the two images, and from this, the direction and amount of defocus can be determined. I can do it.

However, in the conventional device, the image sensor has to have a certain size, so the two images captured on the image sensor are not only shifted in position, but also have different peripheral parts. The result is image data A stored in two shift registers la and lb.4. B is not only misaligned, but also different at the edges, and since the correlation is calculated while rotating the image data of one of them in a ring shape, it is impossible to obtain an accurate phase difference between the images. Ta. To explain this point in detail based on FIG. 2, (a) and (bl) use image data A stored in shift register 1a and image data B stored in shift register 1b, respectively, and focus If they do not match, both image data A and B will be misaligned, so be, rip, .
p/ is also shifted, and both image data A', Bi
(C) shows the image data B in the shift register 1b shifted by α bits.

Therefore, since the peaks P and P'' match, it can be seen that the phase difference between both image takes A and B is α bits, but the portion of 0 to α bits in the image data of (C) is (b
) is the part of β ~ 127 bits in the state of (a
) and (C) do not completely match. That is,
When the correlation is calculated for all image data of 0 to 127 bits, when the image phase difference is zero, that is, the peaks P, P"
The correlation value does not necessarily reach an extreme value when the two match. Therefore, it is difficult to obtain an accurate image phase difference with this device.

However, since this device only moves image data one pit at a time, it also has the disadvantage that it takes time to detect a large focus amount.

In view of the above-mentioned problems, the present invention detects the relative positional relationship using photoelectric output signals of some elements of a photoelectric conversion device, and when the amount of defocus is large, shifts a plurality of the photoelectric conversion devices at a time. The present invention aims to provide an automatic focus detection device that achieves a significant improvement in detection accuracy and detection speed by detecting the relative positional relationship using the photoelectric output signals of the elements, as shown in Figure 3 below. This will be explained based on one embodiment shown in FIGS. 15 to 15. FIG. 3 shows the principle of the pupil division method used in this embodiment, and in (a), 6
is an imaging lens, 7 is a light-shielding plate with an open lower a disposed near the pupil in front of the imaging lens 6, and 8 is an image plane, and an image Q is formed on the image plane 8 when in focus. However, when out of focus, the blurred image Q1 + is shifted in the opposite direction in the direction perpendicular to the optical axis 0 with respect to the image Q corresponding to the front focus and the back focus.
Q2 is formed on the image plane 8. (b) shows the case where the opening lower a of the light shielding plate 7 is moved to the opposite side with respect to the optical axis O. When in focus, an image Q' is formed on the image plane 8, but when out of focus, an image Q' is formed on the image plane 8, but when out of focus, Blurred image Q1 corresponding to front focus and back focus, respectively
'.

Q21 is formed on the image plane 8. Therefore, when the opening lower a of the light shielding plate 7 is moved, for example, from the position (a) to the position fb), the images Q and Q' are at the same position and do not move when in focus, but in the case of front focus, The image moves from Ql to position Q1', and if still in rear focus, moves to position Q2 (Q2'). By providing a so-called image sensor on the image plane 8, the state of the image can be measured.

From the above, it becomes possible to distinguish between front focus and rear focus, and the amount of out-of-focus at that time can be known from the direction and amount of image movement (ie, phase difference).

Figure 4 is an overall view of an embodiment in which the above principle is applied to a microscope, where 51 is a light source and 52 is a condenser. 53 is a stage on which the specimen is placed for observation. 54 is an objective lens; 55 is a beam splitter that guides light to the focus detection system; 156 is a prism that guides a portion of the light to an eyepiece; and 57 is an eyepiece. 58 is a photographic eyepiece lens, and 59 is a film. Up to this point, the optical system is no different from an ordinary microscope. 60 is a relay lens that guides the light from the beam splitter 55 to the detection optical system, 61 is a lens that creates a pupil, and 62 is a lens 6
This is a pupil divider placed at the position of the pupil created by 1. 63 is an imaging lens, and the light passing through this is filtered 6
4 onto an image sensor 65. 66
is a pupil divider drive circuit, 67 is a stage drive circuit,
Each is controlled by a microcomputer 70.

68 is an image sensor driving circuit; 69 is a microcomputer 70 for transmitting image data from the image sensor 65;
This is an interface circuit that inputs to the Reference numeral 71 denotes a console that performs automatic focusing operations and displays in-focus and impossible images. The microcomputer 70 performs all correlation calculations, focus determination, etc. For the correlation calculation, it is preferable to use a calculation-dedicated LSI that has been recently developed and is on the market.

Next, the operation of each part will be explained in detail. Figure 5 shows two specific examples of a pupil splitter that splits the light flux passing through the pupil to form two images, and (a) shows a continuous light section (hatched area) installed on the glass substrate. The pupil 9 is opened and closed alternately in half by rotating it around the axis O, and (b) is a sector-shaped one with an opening 】0, and the pupil 9 is rotated around the axis O.
By rotating left and right around the center, the pupils 9 are alternately opened and closed in half. In case (a), DC
This method is suitable for a method in which an image sensor is used to capture an image in response to a synchronization signal from a pupil splitter that is rotated by a motor or the like. (b) is suitable for a method in which the pupil divider is moved according to a control device such as a microcomputer and an image is taken by an image sensor in synchronization with the movement of the pupil divider. Thus, by using the pupil divider as described above, (a) and (b) in FIG.
), and then (a).

It becomes possible to obtain image data for each of the states (b) using the image sensor.

Generally speaking, the object or specimen to be focused on is not necessarily located at the center of the field of view, so it is desirable that the image sensor cover a wide range of fields, not just the center of the field of view. However, in order to cover the entire field of view, it is necessary to increase the number of elements in the image sensor. This comes from the fact that the pitch of the elements must be set to a certain degree in order to maintain constant focusing accuracy.

This point will be explained below. FIG. 6 is a diagram showing the relationship between the amount of phase difference and the amount of defocus between two images. Here, to simplify the explanation, we will consider a point image. 13 is the optical axis of the optical system, and it is assumed that the point image 11 is formed by the optical system with the number of rear apertures NA'. Now defocus amount δ
If the image sensor 12 is located at position d, there will be two images 11A.

Since 11B is formed with a phase difference of Sp, δd
The relationship between and Sp is as follows. Now let's consider the focusing accuracy when using a 10x night lens. If the NA of the 10× objective lens is 0.40, NA' is 0.04, and from equation (1), δd〒258p
(2) is derived. On the other hand, the depth of focus t of the 10× objective lens is expressed as t = '□ (8) NA' (ε is the circle of least confusion), so ε-0,
05mm (20 lines/mm) resolution K equivalent) t4++
h't=' 1.25mm
(4) becomes. Since focus detection accuracy within this depth of focus is required, δd=--(5) and δa = 0.625mm (
6) Therefore, Sp = 251+m (7
). In order to accurately obtain this amount of image phase difference, the pitch of the diode array of the image sensor 12 must be approximately 25 μm.

As described above, the pitch of the image sensor 12 is determined based on the requirement for focusing accuracy. In this case, if we use an image sensor with 128 diode arrays on the board,
The area covered by the image sensor is 128 x 0.
025 = 3.2mm, which is very small compared to the number of fields of view 21 (field of view is 21mm in diameter), and the object to be focused is moved to the position of the image sensor (generally at the center). It becomes necessary to perform jiao.

FIG. 7 shows the image sensor used in this embodiment and the processing method used therein. In this example, 512
According to this image sensor, an image sensor with a photodiode array of
12X (1,025=12.8mm), which can cover the sharp part of the field of view.

However, if the correlation calculation is performed using all the bits (diode array), the calculation time will be extremely long and it will be meaningless. Therefore, the 512 bits are divided into five blocks a to d of 128 bits, and correlation calculations are performed using the inner blocks of high contrast blocks.

Here, an example of a contrast calculation method will be described. Generally, the evaluation function for contrast evaluation is 'f
It is known that when (x) is the output of the X-th bit of the sensor, it becomes C-Σl f(x) - f (X+1) I or C-Σ(f(X) - f (X+1))2. ing. In the case of this example, unlike river fish matching using the contrast method, which requires accurate knowledge of changes in contrast, it is only necessary to know the relative contrast strength between each block, so it is not necessary to calculate the difference between adjacent bits. There isn't. For example, suppose C-Σ'1f(X)-f(X+5)I (Σ' means to calculate every fourth X -I
f(64)-f(69)l+...+l f (18
4)-f (188) l, which means that it is sufficient to add the absolute value of the difference while calculating it 31 times. Using the conventional calculation method, it would take 121 times.

Note that the reason why the absolute value of the difference between adjacent 5-bit values is calculated every 4 bits is to improve the contrast sensitivity, rather than simply calculating the absolute value of the difference between adjacent values every 4 bits. It's to make things better. Regarding this point, for example, if we perform a comparative calculation based on the light intensity distribution l on the image sensor shown in FIG. 68)-f
(73)l= 113-301+125-601 =52, whereas in the conventional case 0'-1f(64)-f(65)l+1f(68)-f
(69)1=113-141+125-3(] = 6 Therefore, the present example has better contrast sensitivity than the conventional case.

Furthermore, in order to reduce the amount of calculation in total, if you calculate the difference between the adjacent value of X bits and calculate this every X bits, then x>
Y is preferred. In this embodiment, X25>4=Y.

Note that the data used for the function f may be either image data A or B.

Thus, blocks a and b are created in the above manner.

..., calculate the contrast of e and select the one with the best contrast, but as it is clear from Figure 7, blocks a and b overlap at 128 to 192 bits, so 64-12 to avoid unnecessary calculations
8 pit, 128~192 pit l-, 192~2
The contrast of 56 bits may be calculated respectively, and the contrast of block a may be the sum of the contrasts of 64 to 128 bits and 128 to 192 bits, and the contrast of block b may be the sum of the contrasts of 128 to 192 bits and 192 to 256 bits. Furthermore, blocks a, b,
c, a.

The reason why each half of e overlaps is so that even if there is a part with a significant change in image intensity at the block boundary, it is possible to set a block that includes the change.

For example, if there is a significant change in image intensity near the boundary between blocks a and c, that is, around 192 bits, block a
Alternatively, although it is not possible to use all of the information in block C, if block b is set, all of the information will be included in block b, which is convenient. Since the calculation for determining the contrast takes a much shorter time than the calculation for the correlation, the calculation time in this embodiment is about 128-bit correlation calculation time + α. The reason why blocks are not set for 64 bits on each side is to prevent the situation described in FIG. 2 from occurring when the correlation is calculated by shifting the images.

By performing the processing as described above, even if the subject or specimen to be focused is not necessarily in the center of the field of view, the area (block) where the subject is located will be automatically selected and focus detection will be performed.

For the above, there is no need to define a fixed block, and the number of photodiodes required for the correlation calculation can be selected from among the numerous 7-otodiode arrays of the image sensor arranged to cover most of the field of view. All you have to do is select the part that includes the diode array based on contrast, etc. Marks etc. may be manually set in the field of view for close observation.

In this way, even if there is a three-dimensional specimen (or dust) in the field of view, the user can focus on the subject he or she wants to focus on.

Next, the overall operation will be explained. The two image data A and B from the image sensor 65 in FIG.
Stored in memory 0. Then, among the five blocks, a block with high contrast is selected, and a correlation is calculated based on the image data of that block. Temporarily the 7th
Let us proceed with the discussion assuming that block a in the diagram is selected.

In the correlation calculation, image data A and image data B corresponding to two images stored in memory are calculated by relatively shifting them by 1 bit, and the position of the images is determined by determining how many bits have to be shifted before the images overlap. Find the amount of phase difference. One equation of correlation is
For example, ABS represents the absolute value, and the functions fA(X), f
B(X) represents the value of the X-th bit of image data A and B, respectively. Then, for the − set of functions fA and fB, δ
It is said that Further, in this example, -64≦δ≦64. Since the range of δ can be narrowed near the focal point, calculation time can be shortened.

Since the actual value of δ is only taken for each bit of the image sensor, in order to detect it more precisely, the discrete value of the correlation is curve fitted and the pressure points O9 before and after it are used.
It can also be obtained by performing quadratic curve approximation using p and q (Fig. 10).

As a result of the above, it is possible to keep most parts of the field of view in focus and maintain focus accuracy while hardly increasing the calculation time.

In the above example, δ is in the range of -64 to 64, and the defocus amount in this range is 0.625X64=4 from equation (6).
0mm and 1. On the objective side, 40/102= 0-4=
The force and defocus amount is ±400μm.
becomes. If an attempt is made to include a wider range of defocus amounts within the detection range, it is conceivable to increase the range of δ, but this increases the amount of calculation and is not desirable. When the amount of defocus is large like that of Kade, there is no point in performing highly accurate calculations as described above.

Therefore, in this embodiment, contrast and correlation calculations are performed using data for every few bits of data captured as image data. Specifically, if data is used every 5 bits, data f(0
)! f (1), f (2),..., f
(510).

f(0) in f(511)? f(5), f(
IQ 9..., f (505), f (510
) can be considered as the data to be used. In reality, we only use data for every fifth hit during calculations. For example, (8) R(δ)2 Σ lf (96+4n)-fB(96
+4n+δ)+ (9)n,=OA. In this case, since the defocus amount is large and the image is blurred and contains only low frequency components, no block division is performed. In this case, since the variation of δ is also calculated every 5 times, even if the range of δ is, for example, -200≦δ≦200, the number of correlation calculations is 81, which is a small number. The detection range is ±1.25 mm.

As described above, by using image data every few bits, the detection range can be expanded without increasing the amount of calculation. When the amount of defocus is large like this, by calculating every few bits to get close to the focus position, and then performing calculations that take into account the accuracy mentioned above, automatic focusing with a wide focusing range and high focusing accuracy can be achieved. Detection can be performed.

Furthermore, if the amount of defocus is large, move the stage while calculating only the contrast (which requires less calculation) from the image data, and then focus by correlation after the contrast reaches a constant value. good. Since there is a risk that the correlation calculation will calculate an incorrect image phase if the contrast is not above a certain level, it may be used to decide not to perform the calculation if the contrast is lower than that.

In addition, in the case of a device such as a camera that moves an objective optical system to perform focusing, it is not necessary to drive the optical system.

In the case of the above embodiment, the light flux passing through the pupil is divided to obtain two images, so the image data A
and B may be different in quantity.

This is especially likely to be the case if the focusing system is attached. Furthermore, if there is no pupil divider at the pupil position, the amount of light will be uneven between image data A and B as shown in FIG. 12th
The figure is a diagram schematically explaining the unevenness of light amount. In case (a), since the pupil and pupil divider match, each image height, i, j
In contrast, the amount of light passing through the pupil is all equal to a. In case (b), the pupil and pupil divider do not match, so each image height is
The amounts of light passing through the pupils for i and j are a, c, respectively.
This results in non-uniformity and unevenness in the amount of light.

If there is a difference in the amount of light or unevenness in the amount of light as described above, the image data A
The similarity between the two images B and B will deteriorate, and the accuracy of the correlation processing result will drop significantly. Therefore, correction is necessary. One example of correction is a method often used to remove fixed pattern noise from image sensors, in which image data is obtained by exposing an image sensor to uniform light in advance.

Since the image data is the fixed pattern noise itself due to the uniformity of the incident light, if a correction coefficient is created by the inverse number of the image data, then the influence of the fixed pattern noise can be removed by multiplying the image data by the correction coefficient. In the case of this embodiment, when image data A and B are obtained with uniform light passing through the focusing optical system, image data A and B have uneven light intensity as shown in Fig. 11 due to eccentricity, etc. .

Therefore, by creating a correction coefficient using its reciprocal or the like and performing similar processing, the influence of uneven light amount can be removed. Even if there is a difference in the amount of light, the same effect can be obtained by performing the same processing through the optical system. Additionally, fixed pattern noise of the image sensor can be removed. As a specific method for exposing with uniform light, a simple method is to input image data with no sample placed on the stage 53.

As described above, the above correction requires data input using uniform light once. Although it is not a troublesome operation, if you still do not want to input data for correction, you can correct it by calculation. FIG. 13 is a diagram explaining this, in which the y-axis is in the direction of arrangement of the sensor array, and the y-axis is in the direction of the intensity of image data. Image data A.

As can be seen from the explanation of FIG. 12, the value of B can be thought of as a straight line with a certain slope. That's it, eA,
Let it be 1B. Assuming that the slope of the image data lA is β9, the equation for the image data lA can be obtained from y-βAX10, where lA is the average of the light amount of lA. k is determined by the characteristics of the optical system and may be measured in advance. Calculate the average light intensity of image data A and B al)l! Then, the correction coefficient .alpha. is obtained, and thereby the difference in light amount and the unevenness in light amount can be corrected.

As described above, by using uniform light or performing calculations, it is possible to correct and eliminate the effects of eccentricity of the optical system or eccentricity of the pupil, or the effects of misalignment between the pupil and the pupil divider.

As a result, focusing accuracy is improved and the detection range is expanded. Furthermore, the focus detection section can also be used as an attachment. The most significant effect is that objective lenses of various magnifications with different pupil positions can be used.

Furthermore, when many types of objective lenses are used, such as in a microscope, each objective lens has a different pupil position, so it is difficult to correctly install the pupil divider at the pupil position for all the objective lenses. One possible solution to this problem is to provide a plurality of one-child dividers. By providing a plurality of pupil dividers at the pupil positions of each objective lens, the pupils and the pupil dividers are made to coincide. When using one pupil divider, make sure that the other pupil divider does not cut the pupil.
Needless to say, it has been achieved. For example, as shown in FIG. 14, two pupil dividers similar to those shown in FIG. 5 may be connected.

In FIG. 4, the filter 64 is an infrared cut filter or a bandpass filter, and since the spectral sensitivity 1 spectral distribution of the image sensor, light source 51, etc. is different from the relative sensitivity, it prevents the phenomenon of defocus caused by this. play a role.

When controlling and calculating the automatic focusing device as described above, a method using a microcomputer and an arithmetic processing unit is the easiest and cheapest to design.

Regarding this, the explanation will be supplemented with the flowchart shown in FIG. This shows the most basic case. When focusing is started, it is first checked whether the condition of the microscope is suitable for focusing operation, and the type of objective and 3 magnification are determined. This is because, in the case of light intensity unevenness correction, parameters differ depending on the type of objective and magnification, and the conversion coefficient for converting the amount of image phase difference into the amount of stage movement also differs depending on the magnification (see equation (1)). Next, the data of fB and fB are obtained from the image sensor and stored in the memory. Thereafter, the unevenness in light amount is corrected and the image is stored in the memory again. Since the focus may be largely deviated at the start of focusing, the approximate focus position is determined by correlation calculation every 5 bits (see equation (9)). Then, the image phase difference amount determined by the correlation is converted into a stage movement amount, and the stage is moved. So again fA
, f) Obtain the data of 3 and perform correction. Next, block is determined by contrast evaluation. If the contrast is less than a certain value, the reliability of the correlation result is low, so 5-bit correlation is performed again and the stage is moved closer to the focal position. If the contrast does not increase even after repeating several times, the contrast of the sample is too low, and an "impossible" indication is displayed. If the contrast is above a certain level, the correlation is calculated using the determined block, and the stage is moved to focus.

To confirm focus, fA and fB are obtained again and the correlation is calculated. Here, if the image phase difference amount is within the depth of focus, the image is in focus and the stage is not moved. If it is outside the depth of focus, repeat the same operation again.

The above is an explanation of the most basic operation, and the actual program also takes into account fail-safe situations in the event that there is no sample or the machine breaks down.

The amount of image phase difference may also be used to determine when moving from 5-bit correlation to 1-bit correlation. In the case of the previous example -200≦δ≦
200 ranges are calculated every 5th range, but the correlation R(δ
) takes the minimum value if δ is -200≦δ'≦200, the stage is moved by that amount and then the process moves to 1-bit correlation. In this case, it is better to set the determination condition to be smaller than the calculated range of δ, such as -180≦δ'≦180. This is because when the amount of defocus is large, δ' may be determined to take the minimum value erroneously due to noise or the like.

Figure 16 shows the second embodiment, except for the central processing unit...
- shows an example control/arithmetic circuit configured with hardware. To explain this, first, the pupil divider drive circuit 66 operates in response to a focus start signal from the console 7I to obtain image data A from the image sensor 65. The image sensor 65 starts imaging by the sensor drive circuit 68 in synchronization with the pupil splitter 62. At this time, in the case of an accumulation type image sensor (generally, solid-state image sensors are of this type), color readout is performed in order to erase previously accumulated signals. Image data A continuously read out from the image sensor 65 is sent to a sample hold circuit 31. A/D converter 32. The first memory 34 passes through the switch circuit 33
is memorized. Then, the image data A is corrected using correction coefficient data stored in advance in a memory (not shown) and stored in the first memory 34 again. The correction coefficient data is obtained by multiplying the reciprocal of the above-mentioned image data captured by the image sensor with uniform light incident thereon by the average value of the image data A and B at that time.

Consider the case of a 512-bit image sensor.

When both image data A and B are combined, a total of 1024 bits are obtained from 0 to 1023 bits. Image data A is 0 to 511
Image data B is assumed to be 512 to 1023 bits. If the n-th bit of image data obtained with uniform light without a sample is Xn, then n bits k = -h.

Next, when the image data A is stored in the first memory 34,
The i1m divider 62 is in a state of receiving image data B, and the image data B is corrected and stored in the second memory 35 in the same manner as the image data A. The data stored in the first memory 34 is sent to the contrast discriminator 36 for each block shown in FIG. 7, and the block to be used is determined based on the height of contrast. If the contrast of block b' is the highest, 128 is given to the addressing circuit 37. Address shift #! Initial value -32 for r38
The addressing circuit 37 is connected to the first memory 34.
When the address shift circuit 38 specifies 128 of the second memory 35, the address shift circuit 38 specifies the address 96 of the second memory 35. And image data fA (
128) and fB(96) are input into the subtracter 39 and then passed through the absolute value circuit 4o.]fA(128)-fB(96)1 operation is performed. Then, through the adder 41, the memory 4
It can be stored in 2. When the above is completed, the addressing circuit 37
specifies 129 of the memory 34, and the address shift circuit 3
8 specifies 97 in memory 35, and is calculated in the same way thereafter as 1.
fA(129) fB(97)1 is the previous data l fA(t2g)-fB(96) l
and stored in the memory 42. Thereafter, the process is repeated up to address 255 of the first memory 34, and the phase is completed.

When this calculation is completed, the value of the address shift circuit 38 becomes -31, and the following is calculated. And this is the address shift circuit 38
This continues until the value of becomes 31, and the entire correlation calculation is performed. Subsequently, the central processing unit 43 writes the memory 4
2 is compared, and δ for which R(δ) is the minimum is found and used as the amount of phase difference of the image. Accordingly, the stage drive circuit 67 is driven to adjust the focus.

Note that if the defocus amount is large and the phase difference amount of -32≦δ≦31 is insufficient, the address designation circuit 37 specifies 128 in the first memory 34, and the initial value of the address shift circuit 38 is -64. Become. Then, each time the correlation calculation is completed, it increases by 2, and R (64) = l f'A (1
28)-fB(128-64)l +l fA(]30
)-fB(130-64 month-+-・・・・・・・・・
Publication fA(382)-fB(382-64) 1R(-6
2)= . . . R(60) - . . . The following calculation is performed. This corresponds to using every other bit of the image data, and the detection range of the image phase difference is doubled with the same amount of calculation. However, the focusing accuracy becomes 1/2.

As described above, the image phase difference is calculated and the stage drive circuit 67 is driven to adjust the focus, but the above operation may be repeated several times to accurately adjust the focus. Furthermore, console 7
In step 1, focusing is started and focused display is performed.

As described above, the automatic focus detection device according to the present invention performs a correlation calculation using only a part of the image data obtained by the image sensor, and when the amount of defocus is large, the automatic focus detection device according to the present invention performs a correlation calculation using only a part of the image data obtained by the image sensor. Since the correlation calculation is performed using , detection accuracy and detection speed are significantly improved.

It goes without saying that the present invention can also be applied to an automatic focus detection device using two image sensors.

[Brief explanation of drawings]

FIG. 1 is a diagram showing the main circuit of a conventional automatic focus detection device.
2 is a diagram showing an example of image data stored in the conventional shift register, FIG. 3 is a diagram showing the principle of the pupil division method used in an embodiment of the automatic focus detection device according to the present invention, Fig. 4 is an overall view of the above embodiment, Fig. 5 is a front view showing a specific example of the pupil divider used in the above embodiment, and Fig. 6 is a diagram showing the relationship between the amount of phase difference and the amount of defocus between two images. 7 is a diagram showing the image sensor of the above embodiment and the processing method therein, FIG. 8 is a diagram showing an example of the light intensity distribution on the image sensor, and FIGS. 9 and 10 are Diagram showing a highly accurate phase difference calculation method near the focal point, Part 1
FIG. 1 is a diagram showing the unevenness of light amount of image data in the above embodiment, FIG. 12 is a diagram schematically explaining the unevenness of light amount, and FIG.
14 is a perspective view of another pupil divider, and FIG. 15 is a flowchart showing the computer control and arithmetic processing method of the above embodiment.
FIG. 6 is a diagram showing a control/arithmetic circuit of another embodiment. 51... Light source, 52... Condenser lens,
53... Stage, 54. Both objective lenses, 55...
・・Beam splitter-156・Mountain prism, 57・
...Eyepiece, 58...Photography eyepiece, 5
Two...Film, 60...Relay lens, 61
... Lens, 62 ... Pupil divider, 63 ...
Imaging lens, 64...filter, 65...image sensor, 66...pupil splitter 1 drive circuit, 6
7... Stage 5 drive circuit, 68... Image sensor drive circuit, 69... Interface circuit,
7o...Microcomputer, 71...Console. 6] τj'We Agent Yasushi Shinohara;-=l':lii'E! −＋＋＋−
I- 11 Figure 2 Figure 3 r Figure 4 9 Figure 5 10S Figure 19 Figure Oio Figure Oti Figure

Claims (1)

[Claims] Two images formed through different optical paths are individually converted into photoelectric output signals by a photoelectric conversion device comprising a large number of elements arranged, and the relative positional relationship between the two images is detected based on the photoelectric output signals. In an automatic focus detection device that performs focus detection by
An automatic focus detection device characterized in that when the amount of defocus is large, the relative positional relationship is detected using photoelectric output signals of a plurality of shifted elements of the photoelectric conversion device.