JPH07203278A - Picture processing unit - Google Patents

Abstract

PURPOSE:To quickly process picture data with high precision by updating an accumulated sum of a video signal level for each unit area of a block area in following to sequential movement of the block area in the vertical/horizontal direction. CONSTITUTION:A correlation arithmetic processing circuit 18a makes correlation calculation as a motion vector as to binary picture data based on picture data sticked to each other received by a border buffer 17 and a deviation calculation circuit 18b calculates a deviation for sticking. In this case, the circuit 18a stores a video signal level for each unit area of a block area to a register, in which the levels are accumulated and the result is provided as an output. Deviation quantity data as a horizontal/vertical moving quantity, rotation quantity and a zoom rate are inputted to a memory controller 16 controlled by a CPU 21 to correct a write address of the picture data of a frame buffer 4. Thus, the arithmetic operation is simplified and the arithmetic time is reduced.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image handling device, and more particularly, to an image handling device having a function unit for taking in and evaluating contrast information regarding a predetermined block area of image data.

[0002]

2. Description of the Related Art Conventionally, as an image handling apparatus having a function part for taking in and evaluating contrast information about a predetermined block area of image data, one subject image is divided by scanning a movable mirror, A camera that captures the divided subject image with an image pickup element and attaches the image data of the divided subject image to the overlapping portion can generate image data for one subject image. Further, this type of camera can capture high-definition captured image data corresponding to an effectively obtained 1-frame (field) image even if an image sensor having a normal resolution is applied. It is something.

In this camera, the above-mentioned divisional image data is required to be overlapped as close as possible to each other, but it is possible that the combined portion will be slightly misaligned between photographing due to mechanical scanning accuracy. Therefore, it is necessary to detect the deviation amount for each photographing and perform the bonding based on the deviation amount.

Therefore, as shown in FIG. 37, a possible bonding process is performed from the block area P on the first bonding section R11 of the first image-taking screen M11 (see FIG. 3) which is a standard for bonding. The two first and second characteristic regions Ba and Bb to be obtained are located on the second bonding portion R12 of the second photographing screen M12 (see FIG. 3) to be bonded, and Of the two corresponding areas Ba and Bd which have a high correlation and are to be overlapped with each other, and the deviation amount thereof is detected. Then, the characteristic region B is displayed on the first screen.
By moving the second screen relative to each other so that a and Bb and the corresponding areas Bc and Bd of the second screen are overlapped with each other, the photographing screen M10 ( Image data (see FIG. 3) is generated. The above-mentioned areas are superposed on each other by the characteristic area points Ba0 and Bb0 which are the predetermined upper left points of the characteristic areas Ba and Bb and the corresponding area B.
This is performed by matching the corresponding area points Bc0 and Bd0, which are the predetermined upper left points of c and Bd.

The image data stitching technique is not limited to the split photographing type camera for stitching the images, and is also applied as a technique for detecting a shift amount between two subject images, that is, a motion vector amount. It is a thing.

[0006]

In the above-mentioned split screen stitching camera, the characteristic regions Ba and Bb for obtaining the correlation with the corresponding regions are all white (for example,
37), or in the case of a screen in which there is no contrast such as black in the entire area, it is unsatisfactory to search the corresponding area. Therefore, the characteristic regions Ba,
In order to set Bb on the shooting screen, it is necessary to check the contrast state of the corresponding area.

As a checking method, as shown in an enlarged view of the screen area in FIG. 38, a block composed of a block pixel number nB (5 × 5 pixels in this case) having a predetermined number of pixels to be detected. The pixel data Ds of each pixel in the area P is 0, 1 data, in this example, a monochrome image is used, and black is detected as 0 and white is detected as 1 in the data obtained at a predetermined threshold. Then, a cumulative addition value Σp (Ds) which is the sum of the values is obtained as an index indicating the degree of contrast. In this case, it is assumed that the block area P is formed by 5 × 5 pixels, and the added value Σp (Ds)
Is expressed by the following equation. That is, Σp (Ds) = Dk + Dk + 1 + ………… + Dk + 24 …………… (1). Then, the regions P having the value nB which is a predetermined number of pixels, in this case, a value as close as possible to 1/2 of the number of 24 pixels are selected as the characteristic regions Ba and Bb.

Therefore, the cumulative sum value Σp (Ds) of the total sums for each block area is defined as one row of pixel positions in the upper portion or the lower portion of the pasted portion of the first photographing screen. Alternatively, it is changed column by column, and Σ1 (Ds) ... Is obtained from Σ0 (Ds) as shown in FIG. The Σ0 (Ds) and Σ1 (Ds) are expressed by the following equations.
That is, Σ0 (Ds) = D0 + D1 + ………… + D24 ……………… (2) Σ1 (Ds) = D5 + D6 + ………… + D29 ……………… (3).

In this example, the above (2), (3)
Equation, and Σm (Ds
) Is calculated by the above equation (1), and Σp (Ds)
Is searched for a high-contrast region having a high degree of contrast, which is close to 1/2 of the number of pixels nB, and is set as the first characteristic region Ba or the second characteristic region Bb.

FIG. 40 is a cumulative addition arithmetic circuit diagram for performing the above cumulative addition. A region P (p) of pixel m columns × pixel n rows of the image memory 511 designated by the control unit 510.
(= 0) pixel data is cumulatively added by a cumulative adder 512 to obtain a cumulative addition value Σp (Ds). When the cumulative calculation of the region is completed, the reset signal RST is reset, and the calculation for the regions P (p = 1), P (p = 2) ... Is sequentially executed. FIG. 41 shows the image data output signal and RST signal of the memory 511, and the cumulative addition value Σp.
The time chart of the output signal of (Ds) is shown.

However, in the above-described cumulative addition calculation processing by the camera, the calculation of the above formula (1) is performed every time the region p is changed by one row or one column, and the processing time becomes extremely long. Therefore, a method is conceivable in which the cumulative addition value Σp (Ds) is obtained by cumulative calculation using the cumulative addition calculation circuit of FIG. 42 and the first and second characteristic regions are set.

This calculation method is based on the cumulative addition value Σp (Ds)
Is calculated by the following formula. That is, .SIGMA.p (Ds) =. SIGMA.p-1 (Ds)-(Dk + ... + Dk + 4) + (Dk + 25 + ... + Dk + 29) .................... (4) However, in this operation, only the value Σ0 (Ds) in the area P (p = 0) including the first row is subjected to the addition operation according to the equation (1), and thus the equation (2). For the region P (p = 1) after the next one line down,
Follow (4) above. That is, .SIGMA.1 (Ds) =. SIGMA.0 (Ds)-(D0 + ... + D4) + (D25 + ... + D29) ... (5) The calculation shown in (5) is performed. The above (5) is Σ 0 (Ds
), The sum of the pixel data of the first row (D0 + ... +
D4) is subtracted and the sum value of new addition (D25 + ... + D29) is added to obtain the cumulative addition value Σ1 (Ds). The same applies to the following areas. In this way, the degree of contrast for each block area is detected, an area having high contrast is searched, and the first characteristic area or the second characteristic area is set. It is an addition operation circuit diagram. Compared to FIG. 42, the SEL of the control unit 510
This is a circuit in which a multiplier 513 with a changeover switch that can change ± 1 by a signal is added. Other configurations are shown in FIG.
It has the same configuration as. This circuit performs the operation of the above equation (4). FIG. 43 shows a memory 5 based on the circuit of FIG.
11 shows time charts of the image data output signal 11 and the SEL signal, and the output signal of the cumulative addition value Σp (Ds).

However, even in this arithmetic processing,
Every time the detection block area p is changed by one row, it is necessary to perform addition of (Dk + ... + Dk + 4) and (Dk + 25 + ... + Dk + 29) in the equation (4), and the calculation time is very long. turn into. Then, when the number of pixels of the unit area when selecting the first characteristic area or the second characteristic area is increased, the calculation time further extends, and the first characteristic area of the high contrast area in a short time. Or, the second characteristic region cannot be set, and as a result, it takes too much time to obtain the image data forming one frame (field).

The present invention has been made in order to solve the above-mentioned problems, and a calculation for evaluating the degree of image contrast in a block area by sequentially moving the block area to be evaluated can be executed very quickly. An object of the present invention is to provide an image handling device capable of quickly handling high-definition image data.

[0015]

The image handling apparatus of the present invention defines the shape and size as a unit for detecting the image signal level having each predetermined dimension on the screen. Assuming a block area configured by aligning the unit areas in a predetermined direction, the block area is moved at a stop position each time the block area is sequentially moved while forming an overlapping portion before and after the movement. An image handling apparatus having a function unit for evaluating the degree of image contrast in the block area at each stop position by obtaining the sum of the video signal levels for each of the unit areas included in the block area The cumulative addition means for cumulatively adding the video signal level values for each of the predetermined number of unit areas of the block area, and the block by the cumulative addition means. And holding means provided to hold the accumulated value of the video signal level of each unit area of the click regions,
Adder means for obtaining the sum of the values held in the holding means, and the value held in a part of the holding means is sequentially moved following the successive movement of the block area in the vertical or horizontal direction. Corresponding to the holding value updating means for updating to a value newly obtained by the cumulative adding means, the cumulative adding value stored in the holding means is further added by the adding means, Calculate the sum value as the signal level.

[0016]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a main block configuration diagram of a camera showing a first embodiment of the present invention. The camera of the present embodiment is a camera which is an image handling device suitable for recording characters, photographs, etc., such as characters written on a blackboard, books, etc.
It is a split-screen camera that can capture high-definition images. The captured image data forming one frame (field) is formed by dividing the image capturing area of the subject in the horizontal direction of the screen by scanning the movable mirror, and the divided areas are composed of two CCDs arranged vertically. The image pickup optical system 2 having a two-plate configuration is used to take in each divided area. Then, as shown in FIG. 2, the overlapping position of the picked-up images of the divided screen areas M1 to M4 of the areas A to D divided in the horizontal direction is combined to correct the deviation of the scanning position for each photographing, It should be formed as image data of one photographic screen (one frame) M0.

In the divided screens M1 to M4, overlapping bonding regions R1 to R shared by adjacent screens are shared.
Have three. Further, the divided photographed image data of the divided screens M1 to M4 is composed of image pickup outputs of two systems, respectively, and it is necessary to perform the joining process of the images of the upper and lower two screens M1a and M1b. Since there is no deviation, it is not necessary to correct each time of shooting. Further, the captured image based on the main video signal obtained by the above-mentioned bonding process is displayed on the monitor, but is further recorded as image data on the recording medium. A memory card, a floppy disk, a hard disk, a magneto-optical disk or the like can be applied as this recording medium. It can also be output to a printer or the like and printed out.

As shown in FIG. 1, in the present camera, a subject image is scanned by a mirror scanning section 1 composed of a rotating mirror mechanism, and an image pickup optical system 2 having an upper and lower two plates structure is formed for each divided subject area. Image signals are output to the monochrome process circuit 3 for two systems of image pickup signals for each of the divided screens M1 to M4 (see FIG. 2). The output is captured in the frame buffer 4 as image data of a split screen. The frame buffer 4 also performs mirror inversion processing, non-interlace processing, and misalignment correction processing at the time of bonding performed via the first memory controller 16.

Then, the interpolation calculation circuit 5 performs interpolation processing, and the output thereof is processed through the gamma correction circuit 6 and the pseudo halftone correction circuit 7. Then, the image correction output is
It is input to the changeover switch 10 controlled by the image area separation circuit 15. The image data output from the change-over switch 10 is compressed by the compression circuit 11 controlled by the CPU 12 and written in the memory card 22 via the card I / F 13.

The output of the interpolation calculation circuit 5 is a binarization circuit 9 whose threshold is set by the edge emphasis circuit 8 and the CPU 21.
Image data of two pasting portions, which are the overlapping portions of the two divided screens to be pasted in the binarized image signal, are binarized by the second memory controller 19 With the write address being controlled by, the data is written in the boundary buffer 17 which is a memory for calculating the amount of deviation in the bonding described later.

Further, the output of the interpolation calculation circuit 5 is input to an AF (automatic focusing), AE (automatic exposure) processing circuit 14 and an image area separation circuit 15. AF, AE processing circuit 14
Is output to the CPU 21 and automatic focusing or automatic exposure control is executed. Further, the switching operation of the selector switch 10 is controlled by the output of the image area separation circuit 15. That is, the frame buffer 4
When it is determined that the interpolated output from is the natural image data, the output of the pseudo halftone correction circuit 7 is fetched, and when it is determined that it is the character image data, the output of the binarization circuit 9 is fetched. Controlled.

The correlation calculation processing circuit 18a is based on the image data taken in the boundary buffer 17 and the image data of the two bonding portions which are bonded to each other.
At 2, the correlation calculation as the motion vector for the two image data is performed, and the shift amount for bonding is calculated by the shift calculation circuit 18b. The shift amount is based on the previous screen (which is the first sheet in the first bonding process),
The subsequent (second sheet in the first bonding) screen shift is given by the movement amount (horizontal movement amount x, vertical movement amount y), the rotation amount (θ), and the zoom ratio. Details will be described later with reference to the block diagram of FIG.

A movement amount (horizontal movement amount x,
The vertical movement amount y), the rotation amount (θ), and the zoom ratio are calculated by the CPU 2
It is input to the first memory controller 16 controlled by 1, and the write address of the image data of the frame buffer 4 is corrected. The first memory controller 16 also performs mirror distortion correction and non-interlace processing in the frame buffer 4 in addition to the shift amount correction.

Next, regarding the correlation calculation and the shift calculation processing,
This will be described with reference to FIG. 3, which is a diagram showing a bonding screen, and FIG. 4 which is a block diagram around the detection circuit 18 including the correlation calculation processing circuit 18a and the deviation calculation circuit 18b. 3A shows two divided screens M11 and M12 to be pasted together, and FIG. 3B shows a shooting screen M10 which is a screen after pasting. In addition, in the present embodiment, the subject image is divided into four and photographed in FIG. However, in the following description, the process of pasting the two screens together will be described in detail, but the same process is repeated for pasting more screens.

In the state shown in FIG.
In the state after the captured image data of the first image is captured, it is pasted into the boundary buffer 17 with the binarized image data of the pasted portion R11 of the captured screen M11 before the reference (described as the first image). The binary image data of the pasting portion R12 which is an overlapping portion of the subsequent (explained as the second image) photographing screen M12 that should be captured.

Correlation detection circuit 18 constituting detection circuit 18
37a to 43, as described in the pasting process in the camera of the conventional example, in the pasting section R11 of the first shooting screen M11, pixels of m columns × n rows, in this case, A first characteristic region Ba and a second characteristic region Bb having a size of a block region of 5 × 5 pixels are set,
A value that evaluates the degree of contrast of those characteristic regions,
That is, the first corresponding area on the bonding section R12 of the second image-taking screen M12, which is a block area showing an equal value by the cumulative addition value Σp (Ds) obtained by adding the pixel data shown in the equation (4). Bc or the second corresponding area Bd is searched.

Then, in the shift calculating circuit 18b which constitutes the detecting circuit 18, the characteristic region point Ba0, which is a predetermined upper left point on the first characteristic region Ba and the second characteristic region Bb,
Bb0, the first corresponding area Bc and the second corresponding area Bd
A displacement amount at the time of pasting for matching the corresponding area points Bc0 and Bd0 which are the upper left predetermined points is calculated. This shift amount is indicated by a movement amount (horizontal movement amount x, vertical movement amount y), a rotation amount (θ), and a zoom ratio. The camera of the present embodiment is characterized by the method of setting the positions of the first characteristic region Ba and the second characteristic region Bb, but the details of the processing will be described later.

The deviation amount data is output to the first memory controller 16, and the second image data written in the frame buffer 4 is corrected based on the deviation amount. After that, the stitching portion of the second image data is written on the R11 side of the boundary buffer 17, and the stitching portion of the third image data is written on the R12 side, and the operation is repeated. Similarly, the amount of deviation is detected for the divided photographing screens that are taken in thereafter, and the pasting is performed for each.

FIG. 5 is a block diagram showing a portion of the correlation detection circuit 18a of the detection circuit 18 shown in FIG. 4, which outputs the cumulative addition value Σp (Ds). In the camera of this embodiment, when the first and second characteristic regions Ba and Bb are set, calculation is performed by using a register to obtain a cumulative addition value Σp (Ds) regarding the reference detection block region P. Can be simplified, the calculation time can be shortened, and the first and second characteristic regions Ba and Bb can be set quickly.

That is, the detection block area P is the same m columns × n rows of pixels as the block area shown in FIG. 38, in this case 5 × 5 pixels, and cumulative addition is performed by adding each pixel data 0 and 1 thereof. Find the value and move it by a rows. In the present example, the above-mentioned cumulative addition value is obtained by moving each row in the vertical direction. Then, the expressions (2) and (3), or
Calculated value Σ0 (D) as shown in (4), (5), etc.
s), .SIGMA.1 (Ds), ... .SIGMA.p (Ds). At this time, in the case of this embodiment, the partial sum (Dk + ... + Dk + 4) of one row of the block area shown in FIG. The value,
Registers (1) 18a2 and registers (2) corresponding to rows sequentially
18a3, ... Write to register (n) 18a4 and add those values by adder 18a5 to obtain Σp (D
s) is calculated. Since n = 5 in this embodiment, the register (n) will be referred to as the register (5) in the following description.

More specifically, the equation (1) is rewritten to obtain the equation (6). That is, Σp (Ds) = Dk + Dk + 1 + ......... + Dk + 24 = (Dk + ... + Dk + 4) + (Dk + 5 + ... + Dk + 9) + (Dk + 10 + ... + Dk + 14) + (Dk + 15 + … + Dk + 19) + (Dk + 20 +… + Dk + 24) ……………………………………………………………………………………………………………………… (6) Write and add the values of those registers in the adder 18a5 to obtain the cumulative addition value Σ
Output p (Ds). FIG. 6 shows a time chart when the cumulative addition value Σp (Ds) of each area is calculated. An enlarged waveform of memory output and the like is shown in the lower part of the figure. The image data of the target block area is shown in FIG. When the cumulative addition is started, first, pixel data D0 to D24 for the number of pixels m × n in the block area are output from the memory 17, and the addition output at the Q point is registered in each register (1 ) To the register (5). At the time of register switching, the second memory controller 19 outputs a CNT signal to switch the register number order 1 to n, that is, 1 to 5 in which the added value of each row is written. Also, each time, the addition output of the adder 18a1 is reset by the RST signal from the second memory controller 19. Then, the values stored in the registers are added by the adder circuit 18a5 to calculate the cumulative addition value Σ0 (Ds) of the first block area.

Therefore, the second memory controller 19
Output the CNT signal that rewrites the register data,
The register number of the storage destination of the partial sum data is switched from n, that is, from 5 to 1. Therefore, when obtaining the cumulative addition value Σ1 (Ds) in the next block area shifted by one row, the pixel data of one new row, for example, the sum value of D25 to D29 is
It is stored in the register (1). Then, the values stored in the respective registers are added by the adder circuit 18a5, and the cumulative addition value Σ1 (Ds
) Is output. Below, the regions are shifted line by line, and the cumulative addition value Σp is sequentially formed while forming the overlapping portion of the block regions.
Find (Ds).

According to the present embodiment, when the cumulative addition value Σp (Ds) of the block area designated by sequentially moving within the predetermined range is calculated, when the designated position is moved by one line at the overlapping portion of the block areas, , Rewriting the register value,
The cumulative addition value Σp (Ds) can be obtained by a small number of processes in which the sum of pixel data for one row is stored in the register and the value of the register for the number of rows in the block area is added. Therefore, a block region showing high contrast can be quickly detected by the cumulative addition value Σp (Ds), and the region can be selected as the first and second characteristic regions Ba and Bb, and the bonding can be performed with higher accuracy. Can be executed.

FIG. 8 shows the number of calculation processes for obtaining the cumulative addition value Σp (Ds) in the camera of the present embodiment, which is 2
It shows a comparison with the case of the camera described in the example of the technology of the conventional example of the kind. In the figure, m and n are columns of the block area,
The number of rows is shown, and k is the number of search block areas for which the cumulative addition value Σp (Ds) is obtained. As shown in the figure, in the case of the present embodiment, the number of processing times is a fraction.

In the above embodiment, the data extraction unit for obtaining the cumulative addition value Σp (Ds) is one pixel which is a unit of the block area, but the cumulative addition value Σp is several pixels. (Ds) may be obtained. Also, the unit of movement of the block area for calculation does not have to be limited to 1 column and 1 row, and m or a natural number a smaller than n can be used for the block area of m columns and n rows. The unit area (pixel) may be moved in the column or row direction by an amount multiplied by the dimension in the corresponding direction. Furthermore, as a moving direction, other than horizontal or vertical direction,
For example, the concept of the present invention is included regardless of the movement in any direction such as an oblique direction.

Next, the combining process, that is, the first and second characteristic regions B set on the first screen as a reference.
A process of matching a and Bb with the first and second corresponding areas retrieved on the second screen to be bonded and bonding the first and second divided screens will be described.

FIG. 9 is a diagram showing two divided screens M11 and M12 and a screen M10 obtained by pasting them together. This bonding is performed by setting the set first and second characteristic regions Ba and Bb.
And the first and second corresponding areas Bc, B searched on the second sheet
When d is overlapped, the feature points Ba0 and Bb0 on the first and second feature regions Ba and Bb and the corresponding points Bc0 and Bd0 on the first and second corresponding regions Bc and Bd are matched as shown in the figure. And stick together.

FIG. 10 is a diagram showing a bonding state when the first and second corresponding points Bc0 and Bd0 are deviated. 1
For the corresponding points Ba0 'and Bb0' with no positional deviation corresponding to the characteristic points Ba0 and Bb0 on the first screen M13, the second screen M
When the 14 actual corresponding points Bc0 and Bd0 are deviated, the bonding is performed as shown in the figure.

FIG. 11 is a diagram showing a pasting processing state of the above-mentioned screens M13 and M14. As shown in FIG. 11A, first, the first feature point Ba0 and the first corresponding point Bc0 are Shift to match. Then, as shown in (B), the second screen M14 is rotated so that the second feature point Bb0 and the second corresponding point Bd0 are made to coincide with each other and the bonding is performed.

FIG. 44 is a diagram showing the characteristic points and corresponding points of the respective pasting parts of the pasting screen in the conventional split photographing type camera. In this conventional example, the first feature point Ba0 (x1, y1) and the second feature point Bb0 (x2, y2) are located at arbitrary positions in the bonding area R11 of the screen as the reference.
Are set on the xy coordinates. Then, the first corresponding point Bc0 (X3, Y3) and the second corresponding point Bd0 (X4, Y4) corresponding to the area to be superimposed are detected on the XY coordinates. The first feature point Ba0 (x1, y1) and the second feature point Bb0
The inclination angle of (x2, y2) with respect to the y-axis is θ1, and the first corresponding point Bc0 (X3, Y3) and the second corresponding point Bd0 (X4, Y4).
Let θ2 be the angle of inclination with respect to the y-axis. The reference screen and the pasted screen have a predetermined structural static coordinate shift other than the positional shift due to the error of the mirror scan and the hand shake, and the xy coordinate system and the XY coordinate system are, for example, (X, Y) = (x, y) +10 ........... (7) There is a coordinate shift. Therefore, the above X and Y values need to be corrected in (7).

In order to obtain the deviation of the bonding in this conventional example, the difference Δx, Δy between the first characteristic point Ba0 (x1, y1) and the first corresponding point Bc0 (X3, Y3) and the second characteristic point It is necessary to obtain the rotation angle difference Δθ for matching Bb0 (x2, y2) and the second corresponding point Bd0 (X4, Y4). That is, after correcting the equation (7), Δx = X1-X3 (8) Δy = Y1-Y3 (9) Δθ = arc tan {(x2 -X1) / (y2-y1)} + arc tan {(X3-X4) / (Y4-Y3)} ... (10) In this case, the calculation of the value of ??
Since there are two terms of an, the calculation becomes complicated.

Therefore, in the case of the present embodiment, a deviation amount calculation method which can easily calculate the rotation angle difference Δθ is applied.
That is, the first feature point Ba0 (x, y1) on the reference screen M15, such as the two bonding portions M15 and M16 shown in FIG.
After setting, the second feature point Bb0 (x, y2) is set on a line parallel to the y-axis passing through the feature point Ba0. Therefore, the tilt angle θ1 in the above conventional example becomes zero. The first corresponding point Bc0 (X3, Y3) and the second corresponding point Bd0 (X4, Y4) on the pasting portion M16 of the screens to be pasted are obtained in the same manner as in the conventional example. The deviation of the first corresponding point and the rotation angle of the second corresponding point are
After correcting the above equation (7), Δx = X−X3 ……………… (11) Δy = Y1−Y3 ……………… (12) θ = arc tan {(X4−X3 ) / (Y4−Y3)} (13) In this case, the value of Δθ of the rotation deviation needs only to find one arc tan term, which simplifies the calculation and improves the accuracy. The circuit scale also becomes smaller.

The above (11), (12) and (13)
The calculation may be performed by software, but may be performed by a hardware configuration. The arithmetic circuit of FIG. 13 is a block diagram of the shift arithmetic circuit 21a for performing the arithmetic operation, and is composed of four subtractors and a ROM table in which the values of arc tan (a / b) are written.
Further, the shift amount calculation circuit 21a is the CPU of FIG.
21 built in. Then, the outputs Δx, Δy, θ
Is output to the first memory controller 16 and the image data in the frame buffer 4 is pasted.

Next, a modified example of the search processing of the corresponding area of the screens to be pasted corresponding to the contrast state of the characteristic area of the reference screen will be described. FIG. 45 shows a block sum detection process in the conventional example,
For example, the corresponding block area on the pasting screen where the value of the cumulative addition value Σ of the image data 0, 1 in the area of 4 columns × 4 rows matches is designated as the corresponding area. In the case of this figure, the cumulative addition value Σ of the characteristic region B21 on the pasting portion M21 on the reference screen side is 8. Then, the block areas B22, B23, B24 of the pasting portion M22 on the screen side to be pasted
When the cumulative addition value Σ of 0 is checked and the values are 0, 16, and 8, the block area B24 having the cumulative addition value Σ of 8 is designated as the corresponding area.

In the example of FIG. 46, the pattern matching method of the area is applied, and the block area in which the pattern of the image data matches is designated as the corresponding area. In this case, the block area having a pattern that matches the image pattern of the characteristic area B21 specifies the block area B27 of B25, B26, and B27 as the corresponding area.

However, in the case of the block summation method shown in FIG. 45, even if the cumulative addition values Σ coincide with each other, different image patterns may be designated. Figure 4
As shown in the image data of the characteristic region of No. 7 and the corresponding region, as the region where the cumulative addition value Σ coincides with that of the characteristic region B31 where the cumulative addition value Σ is 4, the pattern matching region B32
Corresponding to but different patterns B33, B3
4, B35 is specified as the corresponding area.

Further, in the pattern matching method shown in FIG. 46, as shown in the screen of the characteristic area and the corresponding area of FIG. Even though the characteristic region B36 originally corresponds to the block region, it is determined that the characteristic region B36 does not correspond to the characteristic region B36 because the pattern is relatively inclined.

Therefore, what is proposed as a modified example of the search processing of the corresponding area to the characteristic area in the camera of the above-mentioned embodiment is the processing that uses both the block summation method and the pattern matching method. In this processing, the pasting screen M52 is pasted to the reference screen M51 shown in FIG. 14A, and the combined one shooting screen M shown in FIG.
Get 50. The circuit configuration for executing this processing is substantially the same as the block configuration diagram around the detection circuit shown in FIG. 4, but the detection circuit itself has a block sum detection circuit 18A and a pattern matching detection circuit as shown in FIGS. The difference is that it is composed of 18B.

In this process, first, the image data of the laminating section R51 of the reference screen M51 and the overlapping laminating section R52 of the laminating screen M52 are fetched into the boundary buffer 17. Then, the block sum detection circuit 18A incorporated in the detection circuit 18 of FIG. 15 obtains the cumulative addition value Σ of the characteristic region B51, and the block region having the cumulative addition value Σ corresponding to the value is searched for to find the corresponding region. B52 is designated, and the shift amount including the rotation component θ is detected.

Subsequently, as shown in the block diagram around the detection circuit shown in FIG. 16, a pasting screen of the frame buffer 4 via the first memory controller 16 based on the amount of deviation including the detected rotation component. M52 is rewritten to generate a correction screen M53. After that, further correction screen M
The image data of the bonding section R53 of 53 is transferred to the boundary buffer 17
Take in. Then, the pattern matching detection circuit 18 incorporated in the detection circuit 18 for pattern matching detection between the bonding portion R51 of the reference screen and the bonding portion R53 is performed.
Execute by B.

In this case, since the correction screen M53 is subjected to the rotation correction, the block area which completely corresponds in both the cumulative addition value Σ and the pattern is designated as the corresponding area. As described above, according to this modification, it is possible to search for a block area in which the cumulative addition value Σ matches and also in which the pattern matches, and to search for a corresponding area that completely corresponds to the characteristic area. Then, as shown in FIG. 47, it is possible to exclude from the corresponding area a block area in which the patterns do not match even if the cumulative addition values Σ match.

Next, another modified example of the search processing of the corresponding area of the screen to be pasted corresponding to the contrast state of the characteristic area of the reference screen will be described. FIG. 49 is a diagram showing a detection state of the corresponding area detection processing in the conventional example, in which the first and second characteristic areas A and B when the reference screen M61 and the bonding screen M62 are bonded are detected. It is a figure showing the 1st and 2nd corresponding fields C and D. In this conventional detection process, for the characteristic region A, Δx, Δ
The corresponding area C moved by y is detected, the corresponding area D corresponding to the characteristic area B is detected, and the rotation component θ of the bonded screen is detected.

FIG. 50 is a diagram showing a state in which the reference screen M61 and the bonding screen M62 are bonded to each other. The bonding screen M62 is moved by the movement amounts Δx and Δy, and further, only by the angle θ. Rotate and stick together. In this pasted state, the second characteristic region B and the second corresponding region D do not match because the feature region distance AB and the corresponding region distance CD do not match. In this processing, it is possible that the bonding is performed in the state of such a corresponding area detection error.

Therefore, this modified example is proposed as the corresponding area detection processing in which the above-mentioned problems do not occur. As shown in FIG. 17, the block diagram around the detection circuit in this process is substantially the same as the block diagram of FIG. 4, but the detection circuit 38 is different.

That is, in the detection processing in this detection circuit,
As shown in the flowchart of FIG. 21, first, the allowable value Δd of the difference between the cumulative addition values Σ of the allowable limits recognized as the corresponding areas in the first search is set to 5. That is, if the difference in the cumulative addition value Σ between the characteristic region and the block region is within 5, the block region is treated as the corresponding region. This value Δd is gradually decreased when an appropriate corresponding area cannot be obtained. For example, as shown in the search state diagram of FIG. 18, the cumulative addition value Σ of the characteristic region B55
Is 100, the allowable difference Δd of the difference is set to 5 in the first stage, and when the block areas B56, B57, B58 and the like having the cumulative addition values Σ of 80, 95, 99 are compared, the area B57 is determined as the corresponding area. It is admitted as a target for search. If the allowable difference Δd is set to 4 in the processing step of the next step, which will be described later, only the area B58 is recognized as the search allowable object as the corresponding area.

Then, in the flow chart of FIG. 21, p indicating the block area position for searching the first corresponding area is reset to 0. As shown in FIG. 20, in the bonding section R56, the target area is sequentially changed from C0 to Cp while incrementing p, and the cumulative addition value of the block area Cp to the characteristic area A is changed. It is checked whether the difference of Σ is within a value Δd, in this case, within 5. If it is within 5, the block area Cp is set as the first corresponding area.

Further, q indicating the block area position for searching the second corresponding area is reset to 0. Below, FIG.
As shown in 0, in the bonding section R56, the block area D is sequentially incremented from D0 to Dq while incrementing q.
The target area is changed to, and it is checked whether the difference of the cumulative addition value Σ from the block area Dq with respect to the characteristic area B is within the value Δd, that is, within 5 in this case. If it is within 5, the block area Dq is set as the second corresponding area.

Then, as shown in FIG. 19, the distance between the first and second characteristic regions A and B is compared with the distance between the first and second corresponding regions C and D detected by the above processing. To do. When the distances between the two match, the first and second characteristic regions A and B
Assuming that the first and second corresponding areas C and D corresponding to are detected, the shift amount calculation is executed.

When the distances do not match, the value Δd of the allowable difference of the cumulative addition value Σ is decremented so that the difference between the cumulative addition value Σ and the block area Cp is within the above value Δd. The check and the check as to whether the difference between the cumulative addition value Σ and the block area Dq is within the value Δd is restarted.

When a corresponding area that fits in this way cannot be obtained, the value of the allowable difference is gradually decremented and the search is repeated in the area where the difference between the cumulative addition values Σ is small. Even if the corresponding difference value Δd of the cumulative addition value Σ becomes 0, if the corresponding corresponding areas C and D cannot be detected, error processing such as sounding an alarm indicating that the corresponding area cannot be detected is performed.

In addition to the corresponding area detecting process of the modification shown in the flowchart of FIG. 21, another corresponding area detecting process will be described. This process is performed when the first and second characteristic region intervals do not match the detected first and second corresponding region intervals, as shown in the pasting section of the divided image capturing screen of FIG. Assuming that the selection of the characteristic region on the screen is not proper itself, the AF and AE are redone, the shutter speed, and the threshold value at the time of the binarization process are changed. In that state, the characteristic region is selected and the corresponding region is selected. The detection is performed again.

FIG. 22 is a flowchart of the characteristic region / corresponding region detection processing of this modification. First, the reference screen and the bonding screen obtained by performing the AF and AE processing and the binarization processing are written in the frame buffer, and the bonding portion is captured in the boundary buffer. After selecting the characteristic regions A and B, the corresponding regions C and D are detected. Therefore, the distances between the characteristic regions A and B and the distances between the corresponding regions C and D are compared, and if they match, the detected characteristic regions A and B and the corresponding regions C and D have high compatibility. Then, the shift amount is calculated. If they do not match, the constants such as AF and AE processing, the threshold level in the binarization processing, or
The shutter speed and the like are reset, the image is taken, and the image data is written again. Then, the characteristic region is set and the corresponding region is detected.

In addition to the corresponding area detecting process of the modification shown in the flowchart of FIG. 21, another corresponding area detecting process will be described. This process is shown in the flowchart in FIG. 23. The first and second characteristic region intervals and the detected first and second corresponding region intervals as shown in the pasting section of the divided photographing screen in FIG. Does not match,
The zoom magnification is changed, and the corresponding area detection process is performed based on the changed captured image data.

Further, when the corresponding area cannot be detected by the above detection processing, the detection processing of the flowcharts shown in FIGS.

Next, a description will be given of an image handling apparatus having a motion detecting technique related to the pasting of divided images in the camera which is the image handling apparatus of the embodiment of the present invention. FIG. 51 shows an area enlarged view of a reference image and a target image in a motion detection process of a two-image data screen in a video camera which is a conventional image handling device, and a representative point (feature point).

In this conventional example, a representative point (feature point) matching method is applied, the reference image M71 is an image serving as a matching reference for motion detection, and the target image M72 is an image after movement. And The reference image M71 and the target image M72 are divided into four regions. The representative point area B72 set on each of the four divided screens of the target image M72 is composed of, for example, 8 × 8 pixels. Further, a search area R71 in which the image data corresponding to the representative point area B72 should be searched is set on the four-division screen of the reference image M71.

In this conventional example, the image data of the image is binary data, and the sum of the image data 0 and 1 corresponding to the black and white portions of the representative point area B72, that is,
A block area composed of 8 × 8 pixels equal to the cumulative addition value Σ is detected as a corresponding point in the search area R71 of the reference screen M71, the memory space address of the detected corresponding point area, and the representative point area B72. The amount of movement due to the movement, that is, the amount of deviation is calculated from the memory space address of.

In the case of the above-mentioned conventional example, the representative point area (characteristic area) B72 is set to a fixed position regardless of the contrast state of the pattern of the target image, and a pure white portion or a pure black portion is set. In some cases, it does not necessarily have image information suitable for the search. Therefore, the accuracy of motion detection does not increase. In contrast to this conventional example, the image handling apparatus of this example proposed here can quickly select a high-contrast area as a representative point area on the target image and enables highly accurate motion detection. Is. FIG. 24 is a block diagram of a motion detection unit of the above-mentioned proposed image handling device. As for the image data output from the imaging system, first, the captured image data of the first field is written in the field memory 52 as reference image data. At the same time, the information about the contrast value in the image data of the first field is detected by the contrast detection circuit 51 together with the area information and taken into the motion detection circuit 53.

After that, the picked-up image data of the second field is taken in as the target image data in the motion detection circuit 53, is read from the field memory 52 at the same time, and the reference image data of the first field is taken in in the motion detection circuit 53. .

Therefore, the high-contrast portion is detected from the contrast information for the image data of the first field, which is taken in by the motion detecting circuit 53.
The detection of the high-contrast portion is, for example, to detect the divided area R75 in the divided screen of the image data screen M75 shown in FIG. Then, the position information of the high contrast division area R75 is applied as it is as the high contrast position information for the second image data. This assumes that there is no large shift in the high contrast area between the first and second images, and the contrast information of the first image is used for the second image.

Then, as shown in FIG. 27, the area at the center position of the divided area R75 showing the high contrast for the second target image data is designated as the characteristic area Bf. Further, in the motion detection circuit 53, in the image data of the first reference screen M74, from the image data of the area R76 corresponding to the high contrast area R75, the accumulation indicating the high contrast state of the characteristic region Bf is accumulated. A corresponding block area in which the added value Σ matches is selected as a corresponding area. The amount of movement of the second sheet with respect to the first sheet is calculated from the amount of relative displacement between the corresponding area and the characteristic area Bf, and is output as motion vector information. This motion vector information is stored in the first memory controller 16 shown in FIG.
And the image data in the frame buffer 4 is rewritten.

FIG. 25 is a time chart of the contrast information fetching process of the image data of the motion detecting section of FIG.
Indicates the As the image data, when the target image data is sequentially output as A field data, B field data, ..., Contrast data in each field is taken into the motion detection circuit 53 via the contrast detection circuit 51. At the same time, the image data of each field is also taken into the field memory 52. Immediately after reading the image data and during the vertical synchronizing signal output period, the high contrast position information of the target image is read from the captured contrast data. In the next field period, the CPU outputs the position designation information on the target image.

FIG. 26 is a diagram showing a detailed block configuration of the contrast detection circuit 51 of the motion detection section of FIG. 24 and signal waveforms during each processing. A predetermined high frequency component is extracted from the image data (luminance signal) taken into the detection circuit 51 by a BPF (band pass filter) 51a, processed by an absolute value processing circuit 51b, and then an absolute value processing output is made by a cumulative adder 51c. 27 and the contrast value is added.
The address is written in the contrast data memory 51d at the address corresponding to each divided area. Further, the CPU 51e outputs the position information of the high contrast divided region R75 (see FIG. 27) from the data of the contrast data memory 51d.

FIG. 27 is a diagram showing a divided state of the captured image data screen. In the apparatus of this example,
The contrast detection circuit 51 detects the divided area R75 having the high contrast. Then, the region located in the center of the area is set as the characteristic region Bf.

As described above, according to the image handling apparatus of this example, when setting the characteristic region in the target image, first, the contrast data for each divided area of the target screen is fetched and the high contrast is set in the contrast data. Since the divided area shown is detected and the central area of the divided area is set as the characteristic area, it is possible to specify an ideal high-contrast area for the characteristic area used at the time of detecting the corresponding area later, and highly accurate motion detection. Is possible.

As a modified example of the above-mentioned image handling apparatus with respect to the characteristic region setting method described with reference to FIG. 27, the method shown in FIG. 28 is applied to the high contrast division area R75 detected by the contrast detection circuit 51 of FIG. Further, it is a method of surely searching for an area showing contrast in the area. That is, the area R75 is divided into a predetermined number, for example, 12 as shown in FIG. The divided area Pc
Are sequentially moved to detect the contrast information of each area, and the area showing high contrast is set as the characteristic region Bg. According to this method, the divided area R
Areas showing high contrast in 75 can be reliably searched.

As another modification of the characteristic region setting method, the method shown in FIG. 29 is used in the case where the high contrast divided area R75 detected by the contrast detection circuit 51 of FIG. 24 is searched for a high contrast area. ,
For example, it is assumed that the divided area Pfm consists of columns × n rows of pixels, and the contrast information of each area is detected while sequentially moving the row or column by a pixels, and the area showing high contrast is defined as the characteristic area Bg. Is set as. According to this method, it is possible to surely and finely search a region showing high contrast in the divided area R75.

Next, another example of the image handling apparatus for the motion detection technique related to the above-mentioned division of the divided images will be described. FIG. 30 is a block configuration diagram of the motion detection unit of the proposed image handling apparatus. Note that, in FIG.
The configurations of the image pickup device system and the like other than those shown in are the same as those of the camera of FIG.

The image data output from the image pickup system is processed by the binarization circuit 61, and the binarized image data of the overlapping portion (bonding portion) Rh of the reference first image pickup image data, Binary image data of the overlapping portion (bonding portion) Ri of the second captured image data to be superimposed is written in the boundary buffer 62 as target image data and reference image data.

In the contrast detection circuit 63, a predetermined size in the first area Rh, for example, 100 × 100.
The contrast information of the image data (0, 1) for each block area of the pixel is detected, and the two areas having high contrast are loaded into the motion detection circuit 64 with the positional information of the areas Rh, Ri exhibiting high contrast. Further, in a region smaller than the sizes of the regions Rh and Ri, for example, in a block region of 8 × 8 pixels, a region showing high contrast due to the image data (0, 1) is detected, and the region is divided into two characteristic regions B.
Set as h and Bi.

Further, within the regions Rj and Rk in the second image corresponding to the regions Rh and Ri, search is made for block regions that respectively match the contrast information (cumulative addition value of image data) of the characteristic regions Bh and Bi. Then, two corresponding areas Bj and Bk are obtained. Then, the amount of movement and the amount of rotation when the corresponding regions Bj and Bk of the second screen are overlapped on the characteristic regions Bh and Bi of the first screen are output as displacement amounts. The amount of deviation is the first amount shown in FIG.
It is input to the memory controller 16. Then, the data of the second screen captured in the frame buffer 4 is moved and rotated based on the shift amount to perform superposition.

FIG. 31 shows the contrast detection circuit 6 described above.
3 is a block configuration diagram showing the processing states of the detection circuit of the high contrast region in the motion detection circuit 64. The processing state of this circuit will be described as an operation for detecting contrast data for a block area of 8 × 8 pixels, for example.

Now, considering the contrast data of the image data of the two areas of the search block areas Pi and Pj, the image data is data as shown in FIGS. 32 (A) and 32 (B). First, the cumulative adder 65 of FIG. 31 causes the image data (0,
1) is accumulated and the values 60 and 30 are obtained. In the subtractor 66,
The value 32, which is 1/2 of the number 64 of pixels in the block area, is subtracted from the output values 60 and 30 to obtain the values 28 and -2. The absolute value conversion circuit 67 calculates the absolute value, and the subtracter 68 subtracts the absolute value 28,2 from the value 32 which is ½ of the number of pixels in the block area to determine the contrast height. 4, 30 are output as the contrast data shown. Based on this output value, as the contrast state of the search block areas Pi and Pj, it is determined that the area Pj has a higher contrast and the area Pi has a lower contrast. The contrast data of the block area Pk shown in FIG. 32C shows a state where each pixel is almost black (0) and has low contrast.

Next, still another image handling device having a motion detecting technique related to pasting of divided images will be described. FIG. 33 is a block configuration diagram of the motion detection unit of the above-described image handling apparatus. This detection unit has substantially the same configuration as that shown in FIG. The difference is that the contrast detection circuit 51A is used for AF (automatic focusing) control of the photographing optical system other than the process of detecting the contrast information of the block area of the target image data. The AF section of the AF / AE circuit 14 of FIG. 1 corresponds to the contrast detection circuit 51A.

FIG. 34 shows a division state of the AF area M81 on the photographing screen for AF processing, and one division block is 30 ×.
It is composed of a block region R81 of 96 pixels, and the contrast information of a predetermined region is used for AF control. Further, in the case of this modification, this divided area is used as it is for detecting the characteristic region of the image superimposing processing.

FIG. 35 shows the contrast detection circuit 51.
A has substantially the same configuration as the contrast detection circuit 51 shown in FIG.
The contrast information for F is also output. According to this modification, since the contrast detection circuit 51A is used for both AF control and detection of the characteristic region of the image superposition processing, the circuit scale does not increase.

Next, still another image handling apparatus using the motion detecting technique related to the pasting of divided images will be described. FIG. 36 is a block diagram of the motion detecting unit of the above-mentioned proposed image handling apparatus. This detection unit has substantially the same configuration as that shown in FIG. The difference is that the contrast detection circuit 63A is also used for AF (automatic focusing) control of the photographing optical system, other than the process of detecting the contrast information of the block area of the target image data. However, the contrast detection circuit 63A
In, the image data before being binarized is taken in.

Also in this modification, since the contrast detection circuit 51A is used for both AF control and detection of the characteristic region of the image superposition processing, the circuit scale does not increase.

An apparatus having the following configuration is proposed as an image handling apparatus based on the apparatus of the above-described embodiment or its modification. That is, in one image handling device, an image related to the one region and a region related to the other region that partially overlap each other are overlapped at least in the one region with respect to the overlap region. The areas set as the first characteristic portion and the second characteristic portion in the area are recognized as the first corresponding portion and the second corresponding portion in the overlapping area related to the other areas that should correspond to these areas. An image handling device having a functional unit for detecting a motion so as to be properly overlapped with a region to be processed,
When setting the characteristic part and the second characteristic part, the means for setting each of these parts so that one coordinate position in the Cartesian coordinate system for expressing the coordinate position is the same. According to this image handling device, the detection accuracy (recognition accuracy) and the detection speed are improved, and the calculation circuit scale is reduced.

In another one of the image handling devices, an image related to the one region and a region partially overlapped with each other are related to at least the one region with respect to the overlapped region. The 1st corresponding part and the 2nd corresponding part in the said overlap area | region which the area | region set as the 1st characteristic part and 2nd characteristic part in the said overlapping area | region should correspond to these other areas An image handling apparatus having a functional unit for performing a laminating process so as to properly overlap with a region recognized as, the recognition of the first corresponding part and / or the second corresponding part is performed by the first matching part. Features and / or second
The image related to the one area and the image related to the other area after the first identification operation as to whether or not the accumulated values of the video signal levels in the part to be compared with the characteristic part of It is characterized in that it comprises an identifying means for performing an operation of matching the relative positions of, and then performing a second identifying operation of whether or not the patterns in the part are equal. According to this image handling device, detection accuracy (recognition accuracy) is improved.

Still another one of the image handling devices has an image relating to the one area that partially overlaps and an image relating to the other area in at least the one area depending on the overlapping area. The first corresponding portion and the second corresponding portion in the overlapping area related to the other area to which the areas set as the first characteristic portion and the second characteristic portion in the overlapping area correspond to these, respectively. An image handling device having a functional unit for performing a bonding process so as to properly overlap an area recognized as a unit, the first handling unit and the second handling unit.
When it is discriminated that the distance between the areas recognized as the corresponding portions of the above is different from the distance between the areas set as the first characteristic portion and the second characteristic portion by exceeding a predetermined allowable range, the first characteristic portion is detected. Setting operation of the characteristic portion and / or second characteristic portion by changing the initial condition, recognition operation by changing the initial condition of the first corresponding portion and / or the second corresponding portion, and the above difference Further, means for performing an electronic image magnification variable operation for equalizing both distances, or an operation for sequentially executing two or more operations of the above-mentioned three types of operations is characterized.

Still another one of the image handling devices has an image relating to the one area that partially overlaps and an image relating to the other area in at least the one area with respect to the overlapping area. The area set as one characteristic portion in the overlapping area is properly overlapped with the area recognized as one corresponding portion in the overlapping area related to the other area. An image handling apparatus having a functional unit for performing a matching process, wherein when setting the characteristic part, the region to be set in the characteristic part is divided into a plurality of blocks larger than the characteristic part, A first discriminating operation as to whether or not a predetermined first requirement such as a contrast value of an image corresponding to the setting of the characteristic portion in the block is satisfied is a relatively rough area discriminating operation in each block unit. Then, after that, only the block which is discriminated as the one satisfying the predetermined requirement corresponding to the setting of the characteristic portion in itself by the first discriminating operation is set as the characteristic portion in the in-block area. A setting means is provided for executing a second discriminating operation for identifying a small area satisfying a predetermined second requirement such as a contrast value of a corresponding image as a relatively dense area discriminating operation for the intra-block area. It is characterized by According to this image handling apparatus, the selection of the characteristic portion is quickly performed, so that the processing speed of the apparatus as a whole is improved.

Still another image handling device relates to a first functional unit for identifying whether the image is in a contrast state and evaluating whether it is in a focus state, and the partially overlapping one area. The image and the image related to the other area are related to the overlapping area, and at least the area set as one feature in the overlapping area related to the one area corresponds to the other area. An image handling apparatus having a second functional unit for performing a bonding process so as to form a regular overlap with a region recognized as one corresponding unit in the overlapping region related to the region, wherein the characteristic unit is set. In doing so, it is characterized in that it is provided with means for selecting this characteristic portion from the area identified by the first functional portion as having a contrast of a predetermined level or more. According to this image handling apparatus, the AF means and the means for setting the characteristic portion are partially overlapped and simplified.

[0094]

As described above, the image handling apparatus of the present invention is capable of extremely quickly executing a calculation for evaluating the degree of contrast of an image in a block area by sequentially moving the block area to be evaluated, and a high-definition image is obtained. It becomes possible to handle image data quickly.

[Brief description of drawings]

FIG. 1 is a block configuration diagram showing a configuration of a camera which is an image handling device according to an embodiment of the present invention.

FIG. 2 is a diagram showing a split screen of a shooting screen in the camera of FIG.

3A and 3B show a pasted state of split screens of a shooting screen in the camera shown in FIG. 1, wherein FIG. 3A shows a split screen and FIG. 3B shows a pasted screen.

4 is a detailed block configuration diagram around a detection circuit in the camera of FIG.

5 is a more detailed block configuration diagram of a detection circuit in the camera of FIG.

6 is a time chart of the detection processing of the detection circuit in the camera of FIG.

7 is a diagram showing a moving state of a search block area in the detection processing of the detection circuit in the camera of FIG. 1;

FIG. 8 is a diagram showing comparison of the number of searches for characteristic region detection in the camera of FIG. 1 and a camera separately defined.

9 is a diagram showing a pasted state of divided screens in the camera of FIG.

FIG. 10 is a diagram showing how to combine the divided screens in the camera of FIG. 1;

FIG. 11 is a diagram showing how to combine the divided screens in the camera of FIG. 1;

12 is a diagram showing a characteristic region and a corresponding region of a split screen in the camera of FIG.

13 is a diagram showing an example of an addition circuit of a detection circuit in the camera shown in FIG.

14 is a diagram showing a screen pasting state of a modified example of the detection processing in the camera of FIG.

15 is a part of a block configuration diagram of a circuit of a modified example of the detection circuit in the camera of FIG.

16 is a part of a block configuration diagram of a circuit of a modified example of the detection circuit in the camera of FIG.

17 is a block configuration diagram of a circuit of another modified example of the detection circuit in the camera of FIG.

FIG. 18 is a diagram showing a characteristic region search state of a modified example of the detection process in the camera of FIG. 1;

FIG. 19 is a diagram showing characteristic regions and corresponding regions of screens that are pasted together in a modified example of the detection processing in the camera of FIG. 1;

FIG. 20 is a diagram showing a moving state of a block area for detecting a corresponding area in a modified example of the detection processing in the camera of FIG. 1;

21 is a flowchart of a modified example of the detection process in the camera of FIG.

22 is a flowchart of another modified example of the detection processing in the camera of FIG.

23 is a flowchart of yet another modified example of the detection processing in the camera of FIG.

FIG. 24 is a block configuration diagram of a motion detection unit of an image handling device related to the device of the present invention.

FIG. 25 is a time chart of the contrast data fetching process of the motion detection unit of FIG. 24.

FIG. 26 is a block configuration diagram of a contrast detection circuit of the motion detection unit of FIG. 24.

FIG. 27 is a diagram showing divided block areas for contrast detection in the motion detection section of FIG. 24.

28 is a diagram showing a high-contrast search state in a divided block in a modification of the detection processing of the motion detection unit in FIG. 24.

FIG. 29 is a diagram showing a high-contrast search state in a divided block in another modification of the detection processing of the motion detection unit of FIG. 24.

FIG. 30 is a block configuration diagram of a motion detection unit of an image handling apparatus of another example related to the apparatus of the present invention.

31 is a block configuration diagram of a contrast detection circuit of the motion detection unit of FIG. 30.

32 is a diagram showing image data of a block area applied to the contrast detection processing of FIG. 31.

FIG. 33 is a block configuration diagram of a motion detection unit of an image handling apparatus of still another example related to the apparatus of the present invention.

34 is a diagram showing a division state of a detection target screen in the detection processing of the motion detection unit of FIG. 33.

35 is a block configuration diagram of a contrast detection circuit of the motion detection unit of FIG. 33.

FIG. 36 is a block configuration diagram of a motion detection unit of an image handling apparatus of still another example related to the apparatus of the present invention.

[Fig. 37] Two superposing parts (bonding part) of the bonding screen in the image handling device according to one concept.
FIG.

FIG. 38 is an enlarged view of a block area applied to the characteristic area detection of the combining process in the image handling apparatus according to one concept.

FIG. 39 is an enlarged view of pixels of a block area applied to the contrast information detection for the characteristic area search of the combining process in the image handling apparatus according to one concept.

FIG. 40 is a block configuration diagram of an image data cumulative addition value calculation circuit for a combining process of an image handling device according to one concept.

41 is a time chart of the cumulative addition value calculation circuit of the image handling apparatus of FIG. 40.

FIG. 42 is a block configuration diagram of an image data cumulative addition value calculation circuit for a bonding process of an image handling apparatus according to another concept.

43 is a time chart of the cumulative addition value calculation circuit of the image handling apparatus of FIG. 42.

FIG. 44 is a diagram showing a characteristic region and a corresponding region in the bonding process of the image handling apparatus according to another concept.

FIG. 45 is a diagram showing a state in which a block area corresponding to a characteristic area in a combining process of an image handling apparatus according to another concept is searched.

FIG. 46 is a diagram showing a state in which a block area corresponding to a characteristic area in the combining process of the image handling apparatus according to another concept is searched.

FIG. 47 is a diagram showing a state in which a block area corresponding to a characteristic area in the combining process of the image handling apparatus according to another concept is searched.

FIG. 48 is a diagram showing a state in which a block area corresponding to a characteristic area in a combining process of an image handling apparatus according to another concept is searched.

FIG. 49 is a diagram showing a characteristic region and a corresponding region in the bonding process of the image handling apparatus according to another concept.

FIG. 50 is a diagram showing a bonding state in a bonding process based on the concept of FIG. 49 described above.

FIG. 51 is a diagram showing a target screen and a reference screen to be superimposed in the motion detection process of the image handling device according to another concept.

[Explanation of symbols]

18a1 ……………… Adder (cumulative addition means) 18a5 ……………… Adder (addition means) 19 ……………… Second memory controller (register holding and updating means) Ba ………… ...... First characteristic area (first characteristic portion) Bb …………………… Second characteristic area (second characteristic portion) Bc …………………… First corresponding area (first corresponding portion) ) Bd …………………… Second correspondence area (second correspondence part) B55, Bf, Bg ………… Characteristic area (feature part) P, Pk ………………… Block area

Claims (1)

[Claims] 1. On the screen, unit areas each having a predetermined size and defining the shape and size as a unit for detecting a video signal level are arranged in a predetermined direction. Image of each unit area contained in the block area at each stop position when sequentially moving while forming an overlapping part before and after moving the block area along a predetermined direction. An image handling apparatus having a function unit for evaluating the degree of contrast of an image in a block area at each stop position by obtaining the sum of signal levels, and for each predetermined number of unit areas of the block area. Cumulative addition means for cumulatively adding the video signal level values of, and the cumulative addition value of the video signal level for each unit area of the block area by the cumulative addition means. A holding means provided for this purpose, an adding means for obtaining the sum of the values held by the holding means, and a part of the holding means following the successive vertical or horizontal movement of the block area. An image handling apparatus, comprising: a held value updating means for updating the value held in the value to a value newly obtained by the cumulative addition means in correspondence with the sequential movement.