JP2886882B2 - Autofocus device - Google Patents

Description

Description: BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an automatic focusing device in a camera, for example, and more particularly to an automatic focusing device that enables real-time focus adjustment even for a moving subject.

[Prior art] Conventionally, in a camera equipped with an automatic focusing (AF) device, data corresponding to a focus state is obtained by first integrating an output of a light receiving element for focus detection. Get. This data is input to a microcomputer after A / D conversion, and the microcomputer calculates a defocus amount for the subject. Then, the photographing lens is driven in such a direction as to cancel the defocus amount, thereby achieving focusing.

However, since there is a time delay between the start of the AF operation and the end of driving of the taking lens, if the amount of defocus changes over time due to the movement of the subject, the focus on the subject at the end of driving the lens. Not always. Therefore, in order to keep the subject in focus, it is necessary to repeatedly detect the defocus amount and drive the lens to follow the change in the defocus amount. Such an AF control method is described in, for example, JP-A-60-214325.

Also, JP-A-63-2010, JP-A-63-148218, etc.
A control method is described in which a temporal change rate of the defocus amount is obtained from two defocus amount detection operations separated by time, and this change rate is also considered.

[Problems to be Solved by the Invention] The above-described conventional technology takes into consideration the responsiveness of an AF sensor and a lens driving motor which are mainly used at present, and
It can be regarded as an almost complete AF control method. However, considering that the objective of AF is to always adjust the optical system so that the subject is in focus, it can be said that the control method is still insufficient. Ideally, the focus state is detected in real time, and the result is fed back to the lens driving actuator.

Currently, AF sensor and lens drive motor control
The mainstream is to use a microcomputer. However, when the performance of the AF sensor has improved and the focus state can be detected faster than before, or when the focus state can be detected in real time due to the emergence of a new element, In a control method using a computer, the ability of the AF sensor cannot be fully utilized due to a control speed problem.

As for the lens driving actuator,
A microcomputer is sufficient for controlling a DC motor that is currently mainstream. However, when an ultrasonic motor that has been put into practical use recently is used as an actuator, the responsiveness is significantly improved as compared with a DC motor.
Due to the non-linearity of the control, it is difficult for the control method using a microcomputer to make full use of its capabilities. In particular, when the controlled object has nonlinearity, the nonlinearity is approximately calculated by an equation. However, if accurate control is performed, the calculation becomes very complicated, and the control by the microcomputer is performed. In this case, the control speed is reduced.

The present invention has been made in view of such a problem, and an object of the present invention is to generate a control signal for driving a photographing lens at high speed, so that a moving object can be generated at high speed in real time. It is an object of the present invention to provide an automatic focusing device that enables accurate focus adjustment.

[Means for Solving the Problems] As shown in FIG. 1, an automatic focusing apparatus according to a first aspect of the present invention includes a defocus amount detecting means 2 for detecting a defocus amount of a photographing lens 1 and a defocus amount. Differentiating means 3 for differentiating the defocus amount detected by the detecting means to obtain the differential value, and calculating the differential value from the defocus amount detected by the defocus amount detecting means 2 and the differential value output from the differentiating means 3. Fuzzy inference means 5 for obtaining a control signal of a lens drive actuator 4 for driving the photographing lens 1 as a fuzzy amount, and driving control of the lens drive actuator 4 based on a control signal obtained from the fuzzy inference means 5 Drive control means 6.

As shown in FIG. 2, the automatic focusing device according to the second invention has a defocus amount detecting means 2 for detecting a defocus amount of the photographing lens 1, and a defocus amount detected by the defocus amount detecting means. From the defocus amount detected by the defocus amount detecting means 2 and the differential value output from the differentiating means 3 to determine the moving speed of the photographic lens 1. Fuzzy inference means 7 for obtaining the amount of change as a fuzzy amount; initial speed calculation means 8 for calculating the initial speed of the photographing lens 1; and the output of the fuzzy inference means 7 and the initial speed obtained by the initial speed calculation means 8, A speed calculating means 9 for calculating the moving speed of the taking lens 1 and a lens drive controlling means 10 for controlling the driving of the taking lens 1 based on the output of the speed calculating means 9 are provided. .

An automatic focusing device according to a third aspect of the present invention includes a plurality of light receiving elements that respectively receive light from a subject image passing through different pupils,
Evaluation amount detecting means for detecting the evaluation amount F from the output of the light receiving element, contrast amount detecting means for detecting the subject contrast amount C from the output of the light receiving element, and F / C based on each output of these two detecting means. Calculating means for calculating the value;
Differentiating the F / C value calculated by the calculating means and obtaining the differentiated value; and inputting the F / C value calculated by the calculating means and the differential value output from the differentiating means, Fuzzy inference means for calculating a control signal of a lens driving actuator for driving a photographing lens by inference as a fuzzy amount, and drive control means for driving and controlling the lens driving actuator based on a control signal obtained from the fuzzy inference means; Is provided.

[Operation] The automatic focusing apparatus according to the first aspect of the present invention detects a defocus amount of the photographing lens, obtains a differential value of the defocus amount, and compares the detected defocus amount and the calculated differential value with the antecedent part. The fuzzy inference is performed as an input to calculate the control signal of the lens driving actuator as a fuzzy quantity, and the lens driving actuator is driven and controlled based on the control signal.

An automatic focusing device according to a second aspect of the present invention detects a defocus amount of a photographing lens, obtains a differential value of the defocus amount, and uses the detected defocus amount and the calculated differential value as inputs to the antecedent. By performing fuzzy inference, the amount of change in the moving speed of the taking lens is calculated as a fuzzy amount, the initial speed of the taking lens is calculated, and the moving speed of the taking lens is calculated from the calculated amount of change in moving speed and the initial speed. This is to calculate and drive control the photographing lens based on the calculated moving speed.

An automatic focusing apparatus according to a third aspect of the present invention receives light from a subject image passing through different pupils by a plurality of light receiving elements, detects an evaluation value F from an output of the light receiving element, and detects an evaluation amount F from an output of the light receiving element. Subject contrast amount C
Is calculated, and an F / C value is calculated from the detected evaluation value F and subject contrast value C. Then, after differentiating the calculated F / C value to obtain the differential value, a lens driving actuator that drives the photographing lens by fuzzy inference using the calculated F / C value and the differential value as inputs. The control signal is calculated as a fuzzy amount, and the drive of the lens driving actuator is controlled based on the control signal.

〔Example〕

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

First, before describing the embodiment of the present invention, an outline of fuzzy inference will be described with reference to FIG.
Fuzzy inference is inference using fuzzy rules (fuzzy inference rules) expressed in ambiguous words used by humans in everyday life. The fuzzy rule is "if A =
BIG and B = NORMAL then X = SMALL ".

In FIG. 12, A and B are input variables, and X is an output variable. “A = BIG and B = NORMAL”, which is the part where the conditions for establishing the rule are written, is called the antecedent part, and “X = SMALL”, the concluding part, is called the consequent part. In the fuzzy inference, each input variable is converted into a value of 0 to 1 for calculation, and this conversion is defined by a membership function (antecedent membership function).

Membership functions are defined for each proposition (BIG, NORMAL, SMALL, etc.) handled by fuzzy rules. The degree to which the input variable satisfies each proposition is calculated with reference to the membership function. If there are multiple propositions in the antecedent, find the minimum value. This is called minimum value (MIN) operation. Next, the membership values for each rule are combined.
This compares the consequent part of each rule, takes its maximum value,
This is done by creating a new membership function.
This is called a maximum value (MAX) operation. The center of gravity value of the combined membership function becomes the inference result (output value), and the subsequent control is performed based on the result.

FIG. 12 shows a typical example of the fuzzy inference method, but various other fuzzy inference methods have been proposed.

FIG. 3 shows a first embodiment of the present invention. This embodiment shows a case where a focus detection method of a generally used exit pupil division method is used in a TTL AF camera, for example. That is, the pupil division optical system 14
By receiving via a photographing lens 12 and a half mirror 13 the light from splits the light beam of the exit pupil of the taking lens 12, each of the light beams first line sensor 15 an image by ₁
And directing the second to the line sensor 15 _2.

Data from the line sensor 15 _1, 15 ₂ are respectively sent to the defocus amount calculation unit 16. Defocus amount calculation means 16, the line sensors 15 _1, 15 based on the data from the _2, the image and the second line sensor of the first line sensor 15 on _a 1
5 by calculating the relative displacement between the ₂ on the image, and outputs the defocus amount of the photographing lens 12 (D). This defocus amount calculation method is described in, for example,
Please refer to the publication of 517 publication.

In order to obtain the advantages of the present invention, it is necessary to output the defocus amount in real time or at a speed that can be regarded as substantially equivalent thereto. However, since the line sensor used for AF at present is a charge accumulation type sensor such as a CCD, there is an integration time, and data cannot be extracted in real time. Further, since the correlation calculation for calculating the defocus amount from the extracted data is sequentially performed by the microprocessor, the defocus amount cannot be obtained in real time.

Therefore, it is desirable that the line sensor has an array of photoelectric conversion elements such as SPD (silicon photodiode) and can read data in real time. But SPD
If it is attempted to read data in real time using such a method, it is necessary to increase the area of the element in order to increase the sensitivity, and there is a problem that the resolution is smaller than that of a line sensor such as a CCD.

When a CCD or the like has to be used due to the problem of resolution, it is necessary to improve the sensitivity by minimizing the resolution and to make the optical system brighter, and to approach the real time.

Also, in calculating the defocus amount, dedicated hardware for reading data in parallel and performing collective processing is used in order to reduce the calculation time, and when a microprocessor must be used, high-speed processing is required. A device such as using a dedicated processor is required.

If possible, it would be desirable for the sensor and the arithmetic means to be an analog circuit capable of real-time processing instead of digital processing. Also, the above-described consideration is necessary for the differentiating means 17 for differentiating the defocus amount with respect to time.

Hereinafter, the description will be continued on the assumption that the defocus amount D and its differential value = dD / dt are obtained at a necessary and sufficient speed. The fuzzy inference means 18 outputs the output D of the defocus amount detection means 16.
And the output dD / dt of the differentiating means 17 for obtaining the differential value is used as an input to the antecedent part to perform fuzzy inference, thereby driving the motor (lens driving actuator) for driving the taking lens 12 (the driving speed of the taking lens 12). The amount of change in (moving speed) and the driving direction are calculated. The fuzzy inference means 18 will be described later in detail, and an example in which an ultrasonic motor (hereinafter abbreviated as USM) is controlled based on the output of the fuzzy inference means 18 will be described below.

The speed change signal Δv of the digital value output from the fuzzy inference means 18 is sent to the speed calculation means 19. The speed calculating means 19 newly adds D = v + Δv to the current moving speed v of the photographing lens 12 by adding the change amount Δv to D / D /
Output to A converter 31. The D / A converter 31 is a
Is converted to an analog voltage and input to one input terminal of the differential amplifier 32.

On the other hand, the rotational speed of the USM 33 as a lens driving actuator for driving the photographing lens 12 is detected by an encoder 34, and the output thereof is converted to an analog voltage by an f / v converter (frequency / voltage converter) 35, and the difference is output. The other input terminal of the dynamic amplifier 32 is input. The differential amplifier 32 is a D / A converter 3
The difference between the output of 1 and the output of the f / v converter 35, that is, the speed error signal is supplied to the comparator 36.

The comparator 36 generates a PWM (pulse width modulation) signal by comparing the error signal from the differential amplifier 32 with the output of the triangular wave oscillator 37 as a judgment level, and turns the transistor 38 on and off with the PWM signal. Control. Then, the voltage supplied from the battery power supply 39 through the transistor 38 passes through a smoothing circuit including the diode 40, the choke coil 41, and the capacitor 42, and as a voltage proportional to the on / off ratio of the transistor 38, Applied to the primary coil.

The transistors 43 and 44 boost the voltage of the battery power supply 39 to the voltage required for the USM 33.
45 and transistors 46-49. The pre-driver 45 distributes the pulse supplied from the voltage controlled oscillator 51 to the transistors 46 to 49 so that an alternating current having a phase shifted by 90 degrees is generated, and also outputs the direction signal CCW / CW output from the fuzzy inference means 18. The phase relationship is reversed accordingly.

Then, the alternating current shifted by 90 ° phase shifted by the transistors 43 and 44 is applied to the electrodes 33 ₁ and 33 ₂ of the USM 33 at the resonance frequency.
, The USM 33 rotates at its resonant frequency. U
SM33 resonant state of being monitored by the electrodes 33 _3, the monitoring signal is supplied to the frequency tracking circuit 50. Frequency tracking circuit 50
Controls the oscillation frequency of the voltage controlled oscillator 51 to be appropriate.

Therefore, the USM 33 rotates at a speed according to the calculation result of the fuzzy inference means 18 by the feedback loop. The rotational movement of the USM 33 is converted into a reciprocating movement on the optical axis of the taking lens 12 by a mechanism not shown.

In order to realize the above-described real-time AF, high-speed control of a detection system, a calculation system, and a drive system is required. In addition, high speed is required in order to follow a sudden change of the subject because of real time. In the control based on the conventional binary theory, the control rule must be reduced to increase the speed. However, if the number of control rules is reduced, smooth control operations cannot be performed, and control becomes impossible. Such contradictions exist in conventional methods.

A feature of the control based on the fuzzy theory is a simple control rule. When the fuzzy theory makes a certain amount of judgment, the judgment criteria have a distribution and the different judgments overlap each other, so that the interpolation of the ruleless part can be performed, so that the control rule can be simplified. . In addition, as described in the automatic train operation by fuzzy control which has recently appeared, the fuzzy control operation shows a smooth behavior with human feeling.

As described above, the fuzzy control can be sped up due to the simplicity of the control rules, and can perform smooth control. For these reasons, fuzzy control is suitable for an arithmetic control system of real-time AF.

In the present embodiment, the defocus amount from the defocus amount detecting means 16 and the time differential value of the defocus amount from the differentiating means 17 are taken as inputs to the fuzzy inference means 18, and after the calculation, the speed of the motor drive is calculated. The change amount and its rotation direction are output.

Here, FIG. 4 shows the membership function and its rules in the present embodiment. When the rule shown in FIG. 4 is converted into a linguistic expression “if (consequent part) then (consequent part)”, the following is obtained.

Rule (1): If if D is positively large and is close to zero, then speed change is positively increased.

Rule (2): If if D is slightly larger and is larger, then the speed change is made larger.

Rule (3): If if D is slightly larger and is larger than negative, then the speed change is made slightly larger.

Rule (4): When if D is slightly large in the negative direction and is large in the negative direction, then the speed change is slightly increased in the negative direction.

Rule (5): If if D is slightly large in the negative direction and is large, then the speed change is slightly increased in the positive direction.

Rule (6): When if D is close to zero and is close to zero, then make the speed change close to zero.

Rule (7): If if D is negatively large and is close to zero, then speed change is made negatively large.

The operation from the antecedent part to the consequent part in FIG. 4 is called a minimum value operation, and the smaller of each grade for the input D is taken. According to the value, the membership function of the consequent is the fourth
The head is cut off as shown in the figure, and the area indicated by oblique lines is obtained. Do this for each rule. Next, the sum of the areas of the consequent part membership functions obtained for each rule, which is called a maximum value calculation, is calculated. Finally, an operation called defuzzification is performed to find the center of gravity of the area obtained from the result of the maximum value operation. The value of the center of gravity is output as the speed change amount of the motor rotation. FIG. 5 shows a flow of a series of calculations.

As a means for executing the above-described fuzzy inference, for example, a digital fuzzy circuit disclosed in Japanese Patent Application Laid-Open No. H2-224029 can be used. In this case, if the outputs of the defocus amount calculating means and the differentiating means are input as digital quantities to the fuzzy circuit, and the membership function definition parameters are also input as digital quantities from the microcomputer which controls the fuzzy circuit, an inference result can be obtained. The membership function definition parameters do not necessarily have to be fixed. If the camera is of an interchangeable lens type, parameters unique to the lens are stored for each lens, and the stored values are read out and input as parameters. May be. In the case of a zoom lens, the parameter may be changed according to a change in the focal length.

Further, a combination of a DSP (digital signal processor) and a microcomputer may be used as a substitute for a digital fuzzy circuit.

FIG. 6 shows a second embodiment of the present invention. This embodiment shows a case in which an active type distance detection method using a semiconductor position detecting element (hereinafter abbreviated as PSD) and a light emitting element is used in a non-TTL AF camera, for example. That is, in the distance detecting means 21, the light output from the light projecting element 22 is focused by the light projecting lens
The reflected light is received by the PSD 25
Is formed on the light receiving surface of The PSD 25 is disposed so as to be centered on the optical axis of the light receiving lens 24. When the center of gravity of the imaging point due to the reflected light from the infinite (∞) subject coincides with the center of the PSD 25, the base line length is L, the deviation of the imaging point from the optical axis is X, Assuming that the focal length is f _J and the distance to the subject is l ₀ , Becomes

If the total photocurrent of the PSD 25 is I ₀ and the total length of the PSD 25 is 2t, the photo currents I ₁ and I ₂ due to the reflected light from the subject 11 are Becomes

From the above equation, the photocurrents I ₁ and I ₂ include the distance information 1 / l ₀ . Then, the distance calculating means 26 uses the photocurrents I ₁ ,
Distance l ₀ from I ₂ to the subject is calculated. Method of calculating the distance l ₀ to the subject, for example so are described in detail in Japanese Patent Application Sho 62-310689, see it.

The distance l ₀ calculated by the distance calculating means 26 and the lens position signal
l ₁ is input to the subtracter 27, and the difference signal 1 between them is output. The lens position signal l ₁ is a signal output by the lens position detecting means 28 in accordance with the position of the taking lens 12. Also,
The difference signal 1 output from the subtracter 27 indicates the amount of deviation of the taking lens 12 from the in-focus position. Therefore, the photographing lens 12 may be driven so that the difference signal 1 becomes zero.

The difference signal 1 output from the subtracter 27 is input to the fuzzy inference means 30 and the differentiation means 29. Differentiating means 29 is
The input difference signal 1 is differentiated with time, and the means dl / dt is sent to the fuzzy inference means 30. The fuzzy inference means 30 calculates the drive speed and drive direction of the USM 33 that drives the photographing lens 12 by performing fuzzy inference using the two input signals l and dl / dt as inputs to the antecedent part. Meanwhile, U
The SM 33 drives the taking lens 12 based on the driving speed and the driving direction signal. The USM33 control block is the first
The description is omitted because it is the same as that shown in the embodiment.

In addition to the AF method as described above, a method of measuring the distance from the reflection time of the ultrasonic wave, a double image matching method, or the like may be used.

Next, a method of calculating the defocus amount of TTL AF at high speed will be described. The first image and the second line sensor 15 on ₁
To calculate the relative displacement between the image of the line sensor 15 on ₂ are generally the following two expressions are employed.

However, it is not possible to accurately determine the deviation only with this evaluation formula. Therefore, F (evaluation amount) is obtained by shifting the relationship between the suffixes of Expressions (1) and (2) one by one, and as a function F (s) of the shift amount S, F ( s)
Then, the shift amount S is calculated by finding S that satisfies = 0 and S that satisfies F (s) = minimum value in equation (2). here,
For S, interpolation calculation is performed to find the decimal point, and the error is reduced as much as possible. In this case, if N = 24 and S = 1
If と 24, the calculation in parentheses in the above equations (1) and (2) must be performed (24-1) × 24 times ((1)
Expression). This is the reason why the operation time by the microprocessor becomes longer.

Here, looking at the relationship between F (evaluation amount) and the defocus in the expression (1), it has a certain width as shown by the hatched portion in FIG. The cause is that it is affected by the contrast and the spatial frequency of the subject, and when the defocus is large, that is, when the image is largely blurred, the contrast of the image on the line sensor becomes small. Therefore, by normalizing this F with the total contrast, for example, the sum C of the differences between adjacent sensors, the width becomes considerably small and approaches a straight line. This also
The defocus amount cannot be obtained accurately from the numerical value F / C.

By the way, in the fuzzy inference, if a certain amount of signal is obtained as described above, the feedback will eventually be reduced to a constant value, so that not much accuracy is required. Therefore, when fuzzy inference is used, the F / C amount is sufficient instead of the defocus amount. In this case, the number of operations does not need to be S, so "(24-1) +
Total contrast amount ". The formula for calculating the total contrast is Then, since the basic configuration is the same as the equation (1),
The number of operations converted to equation (1) is (24-1) × 2,
This is 1/12 of the above example. Further, since it is not necessary to perform S, it is only necessary to use a so-called reference unit for the sensor, and it is easier to configure the arithmetic unit with hardware for parallel processing. An example of a block diagram in that case is shown in FIG.

According to the configuration described above, high-speed and accurate AF control that responds to the movement of the subject can be performed.

By the way, in consideration of a change from an initial state, for example, a state in which both the subject and the photographing lens are stopped and a state of being defocused to focusing, the moving speed of the photographing lens is represented by a solid line shown in FIG. The displacement of the taking lens is as shown by the solid line in FIG. 9 (b). In the case of a still camera, the focusing time from the initial state is also important. Therefore, it is desired to give an appropriate initial speed to make it as shown by the dotted line in FIG.

FIG. 10 shows a third embodiment in consideration of the above points. The difference of this embodiment from the first embodiment is that the fuzzy inference means 18 for outputting the speed change amount Δv is the first fuzzy inference means 18 ₁ and the initial speed v ₀ is newly calculated from the defocus amount and its differential value. second fuzzy inference means 18 ₂ to the provided to, and speed calculating means 19, the output v ₀ of the second fuzzy inference means 18 ₂ as the initial velocity, since the first fuzzy inference means 18 ₁ to the current speed v That is, a speed obtained by adding the output Δv, that is, v = v + Δv is output.

Second operation of the fuzzy inference means ₁₈₂ may be the same as the first fuzzy inference means 18 ₁ may be the output v ₀ not Delta] v. However, the scale is different. Therefore, it may be the initial speed v ₀ is multiplied by a coefficient to the output of the first fuzzy inference means 18 _1.

The second input of the fuzzy inference means 18 ₂ is not the defocus amount and the differential value, it is also conceivable to defocus amount and the object speed. In that case, the motor (USM3
The object speed is calculated from the speed of 3) and the differential value of the defocus amount.

Here, the initial speed is not strict, and may be added to the current speed at a very early stage. Further, in the initial state, the case where the differential value of the defocus amount = 0 may be considered depending on the sequence. In this case, the defocus amount does not depend on the initial speed fuzzy inference, as in the fourth embodiment shown in FIG. A method may be used in which the initial speed calculating means 20 for calculating the initial speed v ₀ only from the amount is provided, and the output thereof is input to the speed calculating means 19. In this case, the calculation method may be to make the speed proportional to the defocus amount.

According to the third embodiment (fourth embodiment) described above, an initial speed corresponding to the defocus amount can be given at the start of driving of the photographing lens, as compared with the first embodiment and the second embodiment. Can be remarkably improved in the start-up characteristic at the start of driving.

[Effects of the Invention] As described above in detail, according to the present invention, a control signal for driving a photographing lens can be generated at a high speed based on the defocus amount of the photographing lens and its differential value, and therefore, a moving subject can be generated. On the other hand, it is possible to provide an automatic focusing device that enables high-speed and accurate focus adjustment in real time.

[Brief description of the drawings]

1 and 2 are block diagrams illustrating the present invention, FIG. 3 is a configuration diagram illustrating a first embodiment of the present invention, FIG. 4 is a diagram illustrating an example of a membership function used for fuzzy inference, FIG. 5 is a flowchart for explaining the operation procedure of the fuzzy inference means, FIG. 6 is a block diagram for explaining a second embodiment of the present invention, and FIG. 7 is a diagram showing relative displacement and defocus of images on two sensors. FIG. 8 is a block diagram showing an example of a hardware configuration for calculating a defocus amount at high speed, and FIG. 9 is a diagram showing a change state of a moving speed and a displacement amount at the start of driving of a photographing lens. FIG. 10 is a block diagram illustrating a third embodiment of the present invention, and FIG. 11 is a fourth embodiment of the present invention.
FIG. 12 is a configuration diagram illustrating an embodiment, and FIG. 12 is a diagram illustrating an outline of fuzzy inference. DESCRIPTION OF SYMBOLS 1 ... Photographing lens, 2 ... Defocus amount detecting means, 3 ... Differentiating means, 4 ... Lens driving actuator, 5, 7 ... Fuzzy inference means, 6 ... Drive control means, 8 ... Initial speed calculating means, 9
... speed calculation means, 10 ... lens drive control means.

────────────────────────────────────────────────── ─── Continuation of the front page (56) References JP-A-62-205324 (JP, A) JP-A-56-78824 (JP, A) (58) Fields investigated (Int. Cl. ⁶ , DB name) G02B 7/28 G02B 7/08

Claims (2)

(57) [Claims] 1. A plurality of light receiving elements for respectively receiving light from a subject image passing through different pupils, an evaluation amount detecting means for detecting an evaluation amount F from an output of the light receiving element, and an object from an output of the light receiving element A contrast amount detecting means for detecting a contrast amount C; a calculating means for calculating an F / C value based on each output of the two detecting means; a differential value of the F / C value calculated by the calculating means; Differentiating means for obtaining the F / C value calculated by the calculating means and the differential value output from the differentiating means as inputs, and a control signal of a lens driving actuator for driving a photographing lens by fuzzy inference as a fuzzy amount. Fuzzy inference means for calculating; and drive control means for driving and controlling the lens driving actuator based on a control signal obtained from the fuzzy inference means. An automatic focusing device characterized by the above-mentioned. 2. The automatic focusing apparatus according to claim 1, wherein said fuzzy inference means calculates a driving speed and a driving direction of the lens driving actuator as a fuzzy amount.