JP2974338B2 - Automatic focusing device - Google Patents

Description

Description: TECHNICAL FIELD The present invention relates to a video camera, and more particularly, to an automatic focusing device (AF system) for a video camera.

(Prior art) In recent years, video cameras and other video equipment have been remarkably developed, and miniaturization, automation, and multi-functionality have been achieved in all aspects. As part of this, an automatic focusing device has been used in most video cameras. It has become standard equipment.

There are various types of automatic focusing devices, but video cameras are particularly different from still cameras that capture still images.
Since it is necessary to continuously focus on a moving subject, performance for maintaining a focused state on a moving subject is important.

From such a point of view, as a point of observing the performance of the automatic focusing apparatus, stability and responsiveness can be improved. Stability means that the focusing lens does not operate unnecessarily, that is, from the state of focusing. This means that the focusing lens does not move and does not cause a malfunction such as blurring. The quick response means that when performing focusing, appropriate direction determination and speed control are performed, and the focusing lens is promptly moved to a focused state. A suitable automatic focusing device for a moving image needs to properly balance these two points and realize an appropriate transient response to a change in an image. For this purpose, it is necessary to obtain information for knowing whether or not the current focus state is in focus and reliable motor direction and speed control information.

In recent video cameras, a signal component that changes according to the focus state is extracted from an image signal, and the focus is adjusted based on the signal, because the focus can be adjusted irrespective of the distance of a subject or the like. Tend to be widely adopted.

(Problems to be Solved by the Invention) Currently, there are roughly two types of AF systems of a type that obtains such information from an image signal.

One is a modulation method for performing focus detection by performing optical path modulation, and the other is a trial method.

The former modulation method periodically oscillates a lens or an image sensor with a piezo element or the like to modulate the optical path and positively obtain front-pin, rear-pin information and focus information discrimination information. Although it has the advantage of being able to obtain information on the current in-focus state and the driving direction of the focusing motor, it has the disadvantage of being optically complex and expensive due to the addition of the piezo element and its drive circuit.

In the latter trial method, AF control information such as the moving direction of the focusing lens and the in-focus state is obtained from a changed image signal as a result of driving the focusing motor. First, the focusing lens is slightly shifted (trial).
Therefore, it is called a trial method. This can be realized at a low price without the need for a complicated structure such as a modulation method, but the time required for the trial operation of the focus is longer than that of the modulation method. Since the probability that the determination becomes impossible increases, the ambiguity of the obtained control information increases.

For this reason, in the trial direction, in the binary control in which the focus control information is compared with a simple threshold value and control is performed, if the restart determination is performed after the focus has been performed once, there are many erroneous determinations and the focus is achieved. Nevertheless, the deterioration of the image quality due to the blurring of the image due to the restart of the focusing motor becomes remarkable.

(Means for Solving the Problems) The present invention has been made to solve the above-mentioned problems, and is characterized by a first focus signal that changes according to a focus state from an image pickup signal. Extracting means for extracting a second focus signal having a characteristic steeper than the first focus signal; and differentiating the first and second focus signals output from the extracting means to obtain first and second focus signals. Means for outputting a second differential signal, a focus adjustment speed according to the level of the first focus signal, and a focus adjustment direction based on the current focus adjustment direction and the polarity of the first differential signal. Controlling the focus adjustment speed in accordance with the level of the second focus signal in the vicinity of focusing, and controlling the focus adjustment direction based on the current focus adjustment direction and the polarity of the second differential signal. The second differential signal having a maximum signal level Focus control means for detecting a position where is substantially zero as a focal point, wherein the focus control means is configured such that when the level of the first focus signal is small and the level of the first differential signal is small,
A first rule that defines fast focusing, and
A second rule that defines that when the level of the first focus is low, the level of the first differential signal is high, and the level of the second differential signal is low, the focus adjustment speed is performed at a medium speed; The level of the second focus signal is large,
A third rule that defines that focus adjustment is performed at a low speed when the level of the differentiated signal is large, and the current state of the first and second focus signals and the state of the first and second differentiated signals is An automatic focus adjustment device is configured to determine the focus adjustment speed by calculating a center of gravity of a probability of satisfying a rule.

(Embodiment) Hereinafter, an embodiment of the automatic focusing apparatus according to the present invention will be described in detail with reference to the drawings.

FIG. 1 is a block diagram showing a configuration of automatic focus adjustment in a video camera of the present invention.

In FIG. 1, incident light that has passed through a focusing lens 101 is output as an image signal 103 via an image pickup block 102 including an image pickup device such as a CCD and a signal processing circuit thereof. The image signal 103 is output to the direct and high-pass filter 1
The signal is input to the signal processing circuit 105 via the line 04. In the signal processing circuit 105, a high-frequency signal component as focus determination information of the image,
The normalized edge signals and their composite signals are extracted.

The AD converter 106 AD-converts these signals and supplies the signals to a micro computer (hereinafter, referred to as a microcomputer) 107.
The microcomputer 107 determines the driving speed of the focus motor M for driving the focusing lens from these signals,
Focusing lens 1 via focus driver 108
Control 01. Also, the microcomputer 107 takes in the focal length information and the aperture value information from the zoom encoder 109 and the iris encoder 110 to calculate the depth of field as auxiliary information in determining the driving speed of the focus motor, and uses the information for the speed calculation. I do. This is because the position sensitivity of the focusing lens changes according to the depth of field during the focus adjustment.

FIG. 2 shows the change characteristics of the high-frequency signal component and the normalized edge signal extracted by the signal processing circuit 105 with respect to the focusing lens position. In the figure, 201 indicates a change characteristic of a high-frequency signal component, and 203 indicates a change characteristic of a normalized edge signal. Here, the high-frequency component is a high-frequency component of the luminance signal extracted by the HPF, and the normalized edge signal is, for example, disclosed in Japanese Patent Application Laid-Open Nos. 62-103616 and 62-103616 filed by the present applicant.
As described in detail in JP-A-63-128878, HPF
The signal component corresponding to the width of the edge portion of the subject image obtained by normalizing the differential value obtained by differentiating the high-frequency signal component that has passed through with the contrast is calculated.

Since all of these signals form a peak at the time of focusing, focus control is basically realized by driving the focusing lens toward this peak and performing hill-climbing control.

The difference between the high-frequency signal component and the normalized edge signal is the sharpness of the peak near the focal point. The normalized edge signal forms a steep peak only in the vicinity of the in-focus state, and has almost no peak at a position far away from the in-focus point, so that it has reliable in-focus determination information. On the other hand, the high-frequency component information is set so that a gentle peak is formed and the driving direction of the focusing lens can be determined even when the image is largely blurred.

205 is a differential value of the normalized edge signal when the focusing lens 101 is moved toward infinity, and forms a peak near the focal point. This signal is used to determine whether to stop the focus motor at the time of focusing, as described later.

In the figure, 202 and 204 indicated by dotted lines are the characteristics of the high-frequency signal and the normalized edge signal when the depth of field is deep, and have a gentle slope and a flat characteristic.

Therefore, when the depth of field becomes deep, it is necessary to correct the control data set based on the normal characteristic curves 201 and 203 according to the change in the inclination.

Here, the normalized edge information will be described. FIG. 3A shows an image signal of an edge portion, and FIG. 3B shows a partial waveform thereof. 301 is 302 if the subject is high contrast
Is a waveform representing the signal level in the case of low contrast.

The information required for the focus determination is the width Δx of the inclined portion. Considering the differentiated waveform 303 in FIG.
The height Δh depends on the contrast. Therefore, the face value (S) 304 of the mountain part having the peak point as the apex also depends on the contrast. Considering this waveform as a triangle,
The area S is given by S = Δx · Δh, so that Δx = S / Δh, and a width Δx of the edge slope that is independent of the contrast, that is, normalized, is obtained. Signal processing circuit 105
Performs this arithmetic processing, but since the circuit itself can be realized using the above-described prior example and the like, the description is omitted.

Next, FIG. 4 schematically shows a control algorithm according to the present invention. Basically, there are two control loops. Control the movement of the focus motor in step 1, perform the focus determination in step 2, stop the motor in step 4 if it is in focus, proceed to step 3 if out of focus, and go to step 3 to perform the zero escape routine To return to step 1 via step 2 and continue the motor drive control, and to restart the focus motor that was determined to be in focus and stopped in step 2 This is a restart determination loop in step 5 in which a restart is determined. Then, in the actual control operation, one of the control loops is performed once in one field,
A transition is made between these loops according to the result of each determination routine.

The focus motor control routine shown in step 1 will be described. This performs hill-climbing control of the signal waveform in FIG. 2 as described above. However, the high-frequency signal component and the normalized edge signal, which are input information signals, actually have object dependence, and their waveforms and levels Fluctuates depending on the subject and its environment. As described above, since the information includes ambiguity, the present system uses control by fuzzy inference for controlling the focusing motor. This algorithm is described below.

The ideal focus motor speed control is as shown in the lower part of FIG. 2. In the case of a large blur away from the focal point, the speed is high, and when the focus is close to the medium, the speed changes from medium speed to low speed, and the focus stops at the focal point. It is desirable to do. However, the environment of these velocity distributions is unclear.

In the rules in the fuzzy inference, the relationship between the speed and the input information is made into a rule as shown in table1 in FIG.

Rule 0 is the peak (at the time of focusing) motor stop rule,
Rule 1 (7) is a high-speed hill-climbing rule for large blur, Rule 2 (8) is a fast reversal rule for large blur, Rule 3 (9)
Is the middle-speed hill-climbing rule during middle-blurring, Rule 4 (10) is the middle-speed reverse rule during middle-blurring, Rule 5 (11) is the low-speed hill-climbing rule near focus, and Rule 6 (12) is the low-speed near focus This is a reversal rule. Here, (7) to (12) are rules when the focus motor is moving to the closest side.

The left side of the expression of the conditional part (IF part) is the input information, and the right side is its membership function.

P-Small, P-Big represents a positive value, and N-Small, N-Big represents a negative value. The left side of the output section (Then section) is output information, and the right side is its membership function.

However, among the input information, the focus motor of the hill-climbing rule is the focus motor drive direction of the current (output immediately before performing this inference), and the focus motor of the reverse rotation rule.
Is a focus motor driving direction in which the time from when the output actually reverses from the focus motor output until the result appears in the input information is delayed. The right side of this equation may be given by a membership function or may be given by two values of '1' and '0' according to the accuracy of the focus motor driving direction detecting means.

FIGS. 5 (a), (b) and (c) show the outline of the membership function corresponding to the input / output section of table1. FIG. 3A shows a membership function relating to a normalized edge signal and a high-frequency signal component, FIG. 4B shows a membership function relating to a normalized edge signal partial value and a high-frequency signal differential value, and FIG. It is a membership function related to output, that is, speed.

Here, the calculation method will be described by taking as an example the case where there is input information indicated by △ and ▲. However, at this time, it is assumed that the focus motor is operating in the infinity direction.

In this case, the matching rules are rules 0, 1, and 3 from table1 in FIG. Here, the rule 5 is not used because the condition of “normalized edge signal differential value == P−Big” in the input part of the rule 5 is not satisfied.
This is because the condition of the input unit is not satisfied. The intersection of the membership function on the right side with respect to the input value of each expression in the condition part is the evaluation value of that expression. Since each conditional expression of each rule is && (and) combination in this case, the minimum value in each expression is the evaluation value of the conditional part.

 For example, in rule 1, (rule 1): Focus motor == infinity → 1 High-frequency signal == Small → 0.5 High-frequency signal differential value == P−Small → 0.4, and the evaluation value = 0.4 by AND .

 Similarly, (Rule 0): Normalized edge signal == Big → 0.6 Normalized edge signal differential value == Zo → 0.3, and an AND is obtained to evaluate value = 0.3.

 Similarly, (Rule 3): Focus motor == infinity → 1 High frequency signal == Small → 0.5 High frequency signal differential value == P−Small → 0.4 Normalized edge signal partial value == P−Small → 0.7, By taking AND, the evaluation value = 0.5.

The output in this example is as shown in FIG. That is, the value obtained by multiplying the membership function of the output of each rule by the evaluation value of the above-described condition part is the part indicated by the oblique lines. The actual output is the position of the center of gravity of these shaded portions (marked with ↓).

To explain this calculation further, in the present embodiment, the actual output obtained as a result of obtaining the establishment of the satisfaction of each rule from the membership function is the speed and the driving direction of the focus motor.

FIG. 5 (c) shows the focus motor output (speed and driving direction). At the same time, the motor stop area is the focal point, and as the distance from the focal point increases, the focus motor speed becomes low, medium, It shows that the speed changes at a high speed and the direction is also divided into the infinite direction. This is suitable for the automatic focusing method of the hill-climbing method, in which the driving is performed at a higher speed as the distance from the focal point is increased, the speed is reduced as approaching the focal point, and the driving is stopped at the focal point.

Fuzzy inference, as is well known, computes the degree to which the conditions shown in each rule are satisfied on a membership function, that is, the probability, and obtains an output by integrating these on an output membership function. `` Stop: 0.
Even if the calculation result of `` 3 '' is obtained, the stop process itself is not immediately executed, and the probability of stopping the focus motor is 0.3, so the probability of `` stop '' is 0.3, `` medium speed '' Is 0.5, and the probability of "high speed" is 0.4. As a result of calculating these, the actual driving speed of the focus motor can be obtained.

Therefore, the position of the center of gravity on FIG. 6 is obtained by substituting the probability of satisfying the condition of each of the plurality of rules into the output membership function shown in FIG. Is calculated by calculating the degree of reflection of the condition determined in each rule, and the final focus motor drive speed is determined.

In addition, the calculation method of such a condition evaluation value and an output value is as follows.
Various types can be applied, and the present invention is not limited to the method described above.

By performing the control based on the fuzzy inference as described above, natural focus control can be performed on input information by smooth motor speed and direction control.

Next, a stop determination routine will be described. As described above, the normalized edge signal has a sharp peak near the focus. Accordingly, the differentiated signal also has a peak immediately before focusing (205 in FIG. 2). The focus determination, ie, the stop determination routine in step 2, detects this peak waveform, and stops the focusing motor at the zero-cross point that appears next. And if it is determined to stop, st
Move to the restart judgment loop indicated by ep5.

Next, the zero escape routine shown in step 4 will be described. The fuzzy inference rules routinely used for the focus motor control described above do not necessarily guarantee that one or more rules are satisfied when capturing various natural images.

That is, under special conditions, there is a possibility that the rule does not conform to the inside of the focus motor control loop, and the loop cannot be pulled out with the motor stopped. In such a case, the zero escape routine detects the focus motor speed = 0 and shifts to a restart determination loop.

The restart determination routine of step 5 will be described. If the focus determination is performed in the stop determination routine and the focus motor is stopped, or if the zero escape routine detects that the fuzzy inference rule does not conform, step 5
Shifts to the restart determination loop. At this time, the restart determination routine continuously checks whether or not the image is in focus when detecting a change in the image due to a change in the input information, and restarts when it is determined that the image is out of focus. The control is shifted to and the control is shifted to the focus motor control loop. The determination as to whether or not the subject is in focus is performed by performing a trial operation by moving the focus motor by a very small amount, and determining whether or not the focusing lens is at the peak of the mountain.

As described above, the autofocus algorithm including the fuzzy inference control enables smooth and accurate speed setting and direction control of the focusing lens.

In the above-described system, the high-frequency signal and the normalized edge signal are used as the focus control information. However, the high-frequency signal output from a plurality of high-pass filters may be used without using the normalized edge signal.

FIG. 7 shows a configuration example in this case. The difference from FIG. 1 is that the high-pass filters 701, 702,
.. Are provided, and the signal processing circuit 105 is not required. The A / D converter 106 is used in a time division manner. As for the characteristics of the high-pass filter, as the cut-off frequency increases, a sharper peak is formed near the focus, and the shape becomes closer to a normalized edge signal. However, the dynamic range is much larger. The inference algorithm is the same as that using the normalized edge signal, and is replaced with a high-frequency signal component having a steep peak. However, the setting of the membership function must be adjusted to that.

In this system, since the IC 105 is not necessary for signal processing for calculating a normalized edge signal, it is advantageous in cost.

(Effect of the Invention) As described above, according to the automatic focus adjustment apparatus of the present invention, in an AF system that obtains focus control information from an image signal, focus control is performed by combining a plurality of focus evaluation values in speed control of focus adjustment. The focus state is adjusted step by step by judging the state in detail, so that the optimal focus adjustment speed can always be set for any situation, with good responsiveness, no malfunction, reliability, and stability. A highly automatic focusing operation can be realized.

[Brief description of the drawings]

FIG. 1 is a block diagram for explaining the configuration of an automatic focus adjusting apparatus according to the present invention, FIG. 2 is a characteristic diagram of a focus control signal which changes according to a focus state, and FIG. 3 is a normalized edge signal. FIG. 4 is a flowchart showing an algorithm of control in the present invention. FIG. 5 is a diagram showing a membership function of a fuzzy inference control rule in the present invention. FIG. 6 is a diagram for explaining an example of an output operation by fuzzy inference. FIG. 7 is a block diagram showing another embodiment of the present invention. FIG. 8 is a diagram showing a rule setting table in the speed control algorithm according to the present invention.

Continuation of the front page (58) Field surveyed (Int.Cl. ⁶ , DB name) H04N 5/232 G02B 7/11 G03B 3/00

Claims (2)

(57) [Claims] 1. An extracting means for extracting a first focus signal which changes according to a focus state from an image pickup signal, a second focus signal having a characteristic which is steeper than the first focus signal, and Means for differentiating the output first and second focus signals, respectively, to output first and second differential signals; and adjusting the focus adjustment speed according to the level of the first focus signal.
The focus adjustment direction is controlled based on the current focus adjustment direction and the polarity of the first differential signal, and the focus adjustment speed is adjusted according to the level of the second focus signal near the focal point, and the current focus adjustment direction is adjusted. And a focus for controlling the focus adjustment direction based on the polarity of the second differential signal and the polarity of the second differential signal, and detecting a position where the second signal level is maximum and the second differential signal is substantially zero as a focal point. A first rule that defines that high-speed focus adjustment is performed when the level of the first focus signal is low and the level of the first differential signal is low, and The first
A second rule defining that the focus adjustment speed is performed at a medium speed when the level of the focus signal is low, the level of the first differential signal is high, and the level of the second differential signal is low; A third rule that defines that the focus adjustment is performed at a low speed when the level of the focus signal is high and the level of the second differential signal is high, and the current first and second focus signals and the first rule are defined. An automatic focus adjustment device configured to determine the focus adjustment speed by calculating the center of gravity of the probability that the state of the second differential signal satisfies each of the rules. 2. The method according to claim 1, wherein when the current states of the first and second focus signals and the first and second differential signals do not satisfy any of the rules,
An automatic focus adjusting device, comprising: means for stopping the control by the focus control by the focus control means.