JP2000322511A - Device and method for processing image and computer readable memory - Google Patents

Abstract

PROBLEM TO BE SOLVED: To reproduce an image mixing a character image and an intermediate image with high definition by synthesizing an image signal corresponding to a character, an image signal corresponding to an area image disabled in character recognition and an image signal corresponding to an image excepting a character line. SOLUTION: It is discriminated whether each divided line is a recognizing line capable of character recognition or not (S105). Next, the character recognition is performed to a character segmented from each recognizing line (S106) and the recognized character is converted to font data (S107). The font data are synthesized with image data except the recognizing line (an image binarized by a binarizing processing part based on an error diffusion method) (S108). Namely, when a character within the segmented area can be recognized concerning the recognizing line on which a character pixel exists, the character is expanded into corresponding font data. Even when the character can not be recognized, the existence of a character within the area is recognized by image area separating processing and the simply binarized image signal of highest resolvability is selected and outputted so that the image of satisfactory resolution can be generated.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to an image processing apparatus and method for processing an input image, and a computer readable memory.

[0002]

2. Description of the Related Art The character recognition technology can perform almost real-time processing at a copying speed of a low-speed copying machine due to the recent increase in the speed of CPUs and semiconductors. Further, in recent years, since almost all copied originals are created by a word processor or the like, the recognition accuracy has been improved, and has reached a practical level.

[0003] Regarding the recognition of the character size in a document and the recognition technology of the character, see, for example, Japanese Patent Laid-Open No. 61-10787.
6 and the like, the technique of converting the character image information of the original document into recognized font image information and reproducing the image is used, so that image deterioration due to repeated copying in principle is eliminated.

[0004]

However, in the above-described conventional character recognition technology, a projected image in two directions orthogonal to each other is obtained from the entire binarized document image, an average character size is predicted, and the entire document is calculated using the size. Is divided into meshes corresponding to the character size. In order to perform character recognition on the divided and cut-out characters, if a halftone image is mixed in the original image, the projected image indicating the character string is disturbed by the halftone image. Therefore, there is a problem that the mesh cannot be accurately recognized.

Further, since it is not possible to distinguish a character that cannot be recognized from a character and a part of a general halftone image, the output image signals for both are the same. There is a problem in that the resolution is reduced, and conversely, if emphasis is placed on unrecognizable characters, the gradation of the halftone image is reduced.

SUMMARY OF THE INVENTION The present invention has been made in view of the above problems, and has an image processing apparatus and method capable of reproducing an image in which a character image and a halftone image are mixed at a higher quality, and a computer readable memory. The purpose is to provide.

[0007]

An image processing apparatus according to the present invention for achieving the above object has the following arrangement.
That is, an image processing apparatus that processes an input image, an extraction unit that extracts a character line in the input image, and a cutout unit that cuts out an area image from the character line extracted by the extraction unit. A character recognizing means for recognizing a character in the region cut out by the extracting means, a first generating means for generating a first image signal corresponding to the character recognized by the character recognizing means, A second generation unit configured to generate a second image signal for an unrecognizable region image, a third generation unit configured to generate a third image signal for an image other than the character line in the image, and the first image signal; Output means for combining and outputting the second image signal and the third image signal.

Preferably, the first image signal is:
This is font data corresponding to the character.

Preferably, the second image signal is:
This is a simple binarized image signal.

Preferably, the third image signal is:
This is an image signal that has undergone pseudo halftone processing.

Preferably, the character recognition means includes:
A first determining unit that determines whether a pixel exists at a boundary of a character line adjacent to the attention area image; and, based on a determination result of the first determination means, an area in which the attention area image cannot be recognized. It is determined as an image.

[0012] Preferably, the character recognizing means includes:
A second determination unit configured to determine whether or not the attention area image is character-recognizable based on the number of pixels present in the attention area image, and based on a determination result of the second determination means,
Determining the attention area image as an area image in which characters cannot be recognized.

Preferably, the character recognition means includes:
If the area image adjacent to the attention area image is not character recognizable, the attention area image is determined to be an area image incapable of character recognition.

Preferably, when the image is a multi-valued image signal, the second image signal is an edge-enhanced multi-valued image signal.

Preferably, when the image is a multi-level image signal, the third image signal is a smoothed multi-level image signal.

An image processing method according to the present invention for achieving the above object has the following arrangement. That is, an image processing method for processing an input image, comprising: an extraction step of extracting a character line in the input image; and a cutting step of cutting out an area image from the character line extracted in the extraction step. ,
A character recognition step of recognizing a character in the region cut out in the extraction step, a first generation step of generating a first image signal corresponding to the character recognized in the character recognition step, and a character recognition step of the character recognition step A second generation step of generating a second image signal for an impossible area image, a third generation step of generating a third image signal of an image other than the character line in the image, the first image signal, An output step of combining and outputting the two image signals and the third image signal.

A computer readable memory according to the present invention for achieving the above object has the following configuration. That is,
A computer readable memory storing an image processing program code for processing an input image, wherein a program code of an extraction step for extracting a character line in the input image, and a character extracted in the extraction step A program code of a cutting step for cutting out an area image from a line, a program code of a character recognizing step for character recognizing the area cut out in the cutting step, and a first image corresponding to the character recognized in the character recognizing step A program code of a first generation step of generating a signal, a program code of a second generation step of generating a second image signal for an area image in which characters cannot be recognized in the character recognition step, and a program code other than the character line in the image. A program code of a third generation step for generating a third image signal for the image, the first image signal, the second image signal, and the third image signal; And a program code for an output step of outputting a signal synthesized by.

[0018]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Preferred embodiments of the present invention will be described below in detail with reference to the drawings.

FIG. 1 is a block diagram showing a functional configuration of the image processing apparatus according to the present embodiment.

The original 1001 is converted into an image signal through the image sensor 102 from the lens 101 of the image reading unit 1002. Next, this image signal is supplied to the A / D converter 103.
Is input to the A / D converter, and is subjected to A / D conversion.
Is input to In the image processing unit 1003, the input image signal is subjected to shading correction by the shading correction circuit 104, and then input to the mode switching circuit 105.

In the mode switching circuit 105, an operation unit 116
, The output destination is switched based on the recognition copy mode or the normal copy mode. When the normal copy mode is set, the light density conversion circuit 106 converts the luminance data into recording density data. Next, after the recording density data is binarized by the binarization unit 120,
Output to the image editing unit 107. In the image editing unit 107,
The editing process is performed on the recording density data based on the setting contents of the image processing stored in the RAM 115 in the CPU 113. Then, the edited recording density data is output to the image recording unit 1004.

An image recording unit 1004 includes a control circuit such as a motor for transporting transfer paper and the like, a laser recording circuit unit for writing a video signal input from the image processing unit 1003 to a photosensitive drum, and a development control circuit for performing development. The recording unit 117 is configured to record an image on a recording medium such as recording paper.

On the other hand, when the recognition copy mode is set by the mode switching circuit 105, the output destination of the mode switching circuit 105 is switched to the image recognition unit 4000. The image recognition unit 4000 uses the image buffer memory 118 to
Characters in the document are recognized, and the character code as the recognition result is converted into font data. The details of the image recognition unit 4 will be described later.

The operation unit 116 is connected to the image processing unit 100.
It has various key groups and various LED groups for instructing an image copy operation such as image editing contents, the number of copies, and a magnification ratio for 3 and a display unit for displaying the contents at the time of operation.

Next, a hardware configuration of the image processing apparatus according to the present embodiment will be described with reference to FIG.

FIG. 2 is a sectional view showing a hardware configuration of the image processing apparatus of the present embodiment.

In FIG. 2, reference numeral 1 denotes a document feeder serving as a document feeder, which feeds the placed documents one by one or two.
The sheet is fed to a predetermined position on the platen glass surface 2 continuously. 4
Reference numeral denotes a scanner including a lamp 3, a scanning mirror 5, and the like, which is placed on the platen glass surface 2 by the document feeder 1. When, for example, a copy instruction or a character recognition instruction is given from the operation unit 116, the scanner 4 scans in a predetermined direction (left and right directions in the drawing) to pass the original reflected light through the lens 8 via the scanning mirrors 5 to 7. An image is formed on the image sensor unit 9.

Reference numeral 100 denotes a control unit on which the various circuits shown in FIG. 1 are mounted. Reference numeral 10 denotes an exposure unit that receives an image signal from an image signal control unit (not shown) that generates an image signal based on image data from the image editing unit 107 in the control unit 100, and a light beam corresponding to the image signal. Is irradiated on the photoconductor 11. Developing devices 12 and 13 visualize the electrostatic latent image formed on the photoreceptor 11 with a developer (toner) of a predetermined color. Reference numerals 14 and 15 denote transfer paper stacking units, which stack and store recording media of a fixed size. The recording medium is fed to the position where the registration roller is provided by driving the feeding roller, and is re-fed with the timing of aligning the leading edge of the image with the image formed on the photoconductor 11.

Reference numeral 16 denotes a transfer separation charger, which is a photosensitive member 11
After the toner image developed on the recording medium is transferred to the recording medium, the toner image is separated from the photoreceptor 11 and fixed by the fixing unit 17 via the transport belt. Reference numeral 18 denotes a paper discharge roller, which stacks and discharges the recording medium on which the image formation has been completed on the tray 20. Reference numeral 19 denotes a directional flapper, which switches the transport direction of the transfer-receiving sheet on which the image formation has been completed between the paper discharge port and the internal transport direction, and prepares for the multiplex / double-side image forming process.

Next, the appearance of the operation unit 116 of this embodiment will be described with reference to FIG.

A power switch 5001 controls power supply to the apparatus main body. A reset key 5002 operates as a key for returning to the standard mode during standby. Reference numeral 5003 denotes a copy start key. 5004
Is a clear key used to clear numerical values such as the number of copies.

Reference numeral 5005 denotes an ID key. The ID key 5005 enables a specific operator to perform a copying operation.
005 makes it possible to prohibit a copying operation unless an ID is input. A stop key 5006 is used to interrupt or stop copying. Reference numeral 5007 denotes a guide key, which is used when the user wants to know each function.

An upper cursor key 5008 is used to move the pointer upward on each function setting screen. Reference numeral 5009 denotes a down cursor key which is used to move a pointer downward on each function setting screen. 501
A right cursor key 0 is a key for moving the pointer to the right on each function setting screen. A left cursor key 5011 is a key for moving the pointer to the left on each function setting screen. 5012 is an OK key,
This key is used to instruct the finalization of processing in each function setting screen.

An instruction key 5013 is a key for instructing execution of the content of the image output to the lower right of the screen 5052 in each function setting screen. A standard size reduction key 5014 is used to reduce the standard size to another standard size. Reference numeral 5015 denotes a 1: 1 copy key, which is used to select 1: 1 copy. A standard enlargement key 5016 is used to enlarge the standard size to another standard size. A cassette selection key 5017 is used to select a cassette stage to be copied.

Reference numeral 5018 denotes a copy density adjustment key which is used to reduce the copy density. An AE key 5019 is used to automatically adjust the copy density with respect to the original density. A copy density adjustment key 5020 increases the copy density. 5021 is a key for specifying the operation of the sorter. Reference numeral 5022 denotes a preheating key, which is used to turn on / off a preheating mode. Reference numeral 5023 denotes an interrupt key, which is used when an interrupt is required to be performed during copying. Reference numeral 5024 denotes a numeric keypad, which is used to input numerical values.

Reference numeral 5025 denotes a marker processing key for setting trimming, masking, and partial processing (contour processing, halftone processing, shadowing processing, negative / positive processing). Reference numeral 5026 denotes a pattern processable key which is used to express a color in a pattern or to express a color by a density difference. 50
A color erasing key 27 is used to erase a specific color. An image quality key 5028 is used to set the image quality. 5029 is a negative / positive key,
Used when performing negative / positive processing. Reference numeral 5030 denotes an image create key which is used when performing contour processing, shadowing processing, halftone processing, italic, mirror processing, and repeat processing.

Reference numeral 5031 denotes a trimming key used to designate an area and perform trimming. 5032
A masking key is used to designate an area and perform masking. Reference numeral 5033 denotes a partial processing key, which is used to designate an area and then perform partial processing (contour processing, halftone processing, shadowing processing, negative / positive processing). Reference numeral 5034 denotes a frame erasing key, which is used when erasing a frame in accordance with a mode. The modes include sheet frame erasing (creating a frame for the sheet size), document frame erasing (creating a frame in accordance with the document size. Document size is specified), and book frame erasing (according to the spread size of the book). Create a blank in the frame and center. Book spread size specified). A binding margin key 5035 is used to create a binding margin at one end of a sheet.

Reference numeral 5036 denotes a movement key for moving an image in a desired area, which is used when moving is desired.
The movement includes parallel movement (up, down, left and right), center movement, corner movement, and designated movement (point designation). 5037
Is a zoom key, which can set a copy magnification from 25% to 400% in increments of 1%. Further, the main scanning and the sub-scanning can be set independently. The magnification of the image is controlled by controlling the moving speed of the scanner 4 in the sub-scanning direction of the document, and the image data read out from the scanner 4 is thinned out or interpolated in the main scanning direction of the document. Do with.

Reference numeral 5038 denotes an automatic scaling key, which automatically enlarges or reduces the size according to the size of the copy sheet. In addition, the main scanning and the sub-scanning can be automatically scaled independently. Reference numeral 5039 denotes an enlargement continuous shooting key, which is used when one original is enlarged to a plurality of copies and copied. Reference numeral 5040 denotes a reduced layout key, which is used when copying a plurality of originals by enlarging / reducing them. Reference numeral 5043 denotes a continuous shooting key which is used to divide a copy area on the glass surface of the original platen into two right and left sides and perform continuous copying (page continuous shooting, double-side continuous shooting) for automatically making two copies. Reference numeral 5044 denotes a double-sided key which is used to output both sides (single-sided double-sided, page continuous double-sided, double-sided double-sided).

Reference numeral 5045 denotes a multiplex key.
Use when you want to perform (page continuous multiplexing). 5046
Is a memory key, which is used to perform a mode using a memory (memory synthesis, area synthesis, watermark synthesis). A projector key 5047 is used when using the projector. Reference numeral 5048 denotes a printer key, which is used when setting for a printer. 50
Reference numeral 50 denotes a mixed original key, which is used when originals are mixed when taking a copy using a feeder. Reference numeral 5051 denotes a mode memory key, which is used for registering the copy mode set for copy, when calling the registered copy mode.

Reference numeral 5052 denotes a liquid crystal display with a touch panel, which displays the status of the apparatus, the number of copies, the copy magnification, and the copy paper size, and displays the mode settings of the recognition copy mode or the normal copy mode and the contents of the set copy mode. indicate.

Next, a detailed configuration of the image recognition unit 4000 of the present embodiment will be described with reference to FIG.

First, in the recognition copying mode, the binarizing unit 1
Numeral 20 includes a binarization processing unit using an error diffusion method and a simple binarization processing unit using a fixed threshold value. The recording density data from the light density conversion circuit 106 is binarized using both of the processing units. The binarized signal is stored in the image buffer memory 118. On the other hand, the luminance data from the mode switching circuit 105 is input to the image area separation unit 119, and the input luminance data is determined for each pixel to determine whether or not the pixel of interest is a pixel constituting a character. Attribute determination signal (1 bit) shown in FIG. This attribute determination signal is also stored in the image buffer memory 118. In particular, since the image area separation unit 119 generally detects an edge part pixel of a character as a character part pixel, for example, a small character of 8 points or less is replaced with a character part pixel regardless of density. Is generated. For a large character or line segment having a large line width, "1" is generated as an attribute determination signal indicating that only pixels constituting the outline indicate a character part pixel.

Here, the image area separation section 119 can use a well-known image area separation technique disclosed in, for example, Japanese Patent Application Laid-Open No. 62-107570. More specifically, the target multi-valued pixel signal is binarized by an average value obtained from its peripheral pixel signals, the two-dimensional continuity of the binarized binarized signal, and the average value obtained at the time of binarization. The character portion is identified and separated from another halftone dot image or a continuous halftone image such as a silver halide photograph from the level difference between the halftone image and the pixel signal of interest.

The image signal stored in the image buffer memory 118 is projected by a character cutout unit 108 in two orthogonal directions on a black pixel in the image signal based on an attribute determination signal as a result of image area separation. The presence of a row or a column in the image signal is detected from the histogram. Then, the whole area of the image signal is divided into rows or columns of a fixed width according to the direction of the detected row or column, each character in the row is cut out for each row, and the feature amount is sequentially determined for each cut out character. It is calculated by the vector calculation unit 109. When the feature amount of the extracted character is input to the recognition control unit 111, the character is recognized using the recognition dictionary of the recognition control unit 111. The details of the processing of the recognition control unit 111 will be described later.
Then, the output recognition character is passed to the image data conversion unit 110 and is converted into font data corresponding to the recognition character.

Next, the processing flow of the image recognition unit 4000 will be described with reference to FIG.

FIG. 4 is a flowchart showing the processing flow of the image recognition unit of this embodiment.

First, in step S109, the image area separating unit 1
Reference numeral 19 performs image area separation processing on the input luminance data, and accumulates an attribute determination signal as a processing result in the image buffer memory 118. In an image portion other than a character, an attribute determination signal “0” is obtained for each pixel. However, in an edge portion or the like in a halftone image, a pixel erroneously determined to be a character exists in isolation. Therefore, in step S110, the erroneous determination pixel (isolation determination pixel) determined to be isolated from the character is removed. As a result, for almost all images, the attribute determination signal “1” is obtained for pixels of only the character portion.

In step S100, the image for one page obtained by the processing in step S110 is stored in the image buffer memory 118. Next, in step S101,
For the image stored in the image buffer memory 118, the projection of black pixels in the X and Y directions is calculated based on the attribute determination signal to create a histogram.

For example, when an image as shown in FIG. 5 is stored in the image buffer memory 118, that is, as an image configuration, for an image having a picture at the top and a horizontal writing document at the bottom, If a histogram is created based on the attribute determination signal, the histogram in the vertical direction of the paper does not have a separation portion corresponding to a row / column, but the histogram in the horizontal direction of the paper can detect the presence of a horizontal line at the bottom of the paper. , A detection result as shown in FIG. 6 can be obtained. That is, the histogram of black pixels in both directions is binarized by a predetermined threshold value, and if regularity at a fixed period can be detected, the existence of a row / column with respect to the sheet can be determined. FIG. 7 shows the character line portion of FIG. 6 in more detail.

Next, in step S103, the line /
Determine the average row height G / average character height V for the columns.
That is, as shown in FIG. 7, the average period G is obtained from the horizontal black pixel histogram, and this is the line height including the space between lines. Also, the average character height V is obtained in the same manner. Then, in step S104, the entire image is divided into strips using the obtained average row height G. In the example of FIG. 6, the data can be divided into 27 rows from L1 to L27.

Next, in step S105, it is determined whether or not each of the divided lines is a recognized line in which characters can be recognized. For example, in the example of FIG. 6, the rows L1 to L13 and L27
In the case of the row, there is obviously no black pixel in each row, so that it is determined that the area is an image area other than a character. On the other hand, since the row L16 has no black pixel at the boundary between the adjacent rows L15 and L17, these rows can be determined to be recognized rows.
That is, whether or not the divided strip-shaped area is a recognition line is
It can be easily determined from the presence or absence of a black pixel on the boundary line. Here, the lines L14 and L15 are recognition lines different from character lines of average size, but are excluded from recognition targets in this case. It is also possible to determine that the lines L1, L13, and L27 are blank areas. In this case, the rows L1, L13, and L27 may be handled as white image areas or as a set of blank characters.

Next, in step S106, character recognition is performed on characters cut out from each recognition line. Next, in step S107, the recognized character is converted into font data. Next, in step S108, the font data and the image data other than the recognition line (the image binarized by the binarization processing unit using the error diffusion method) are synthesized. Therefore, in FIG. 1, the image data conversion unit 110 expands the font data from the recognized character obtained by the recognition control unit 111 when the target line is a recognition line, and also, when the target line is image data, the image buffer memory. From 118, the image signals binarized by the binarization processing unit using the error diffusion method are switched to each other and output to the image editing unit 107.

By the above processing, in the case of the example of FIG. 6, each row from the row L13 to the row L26 becomes a recognized row. Also,
For pixels in each row that is not a recognition row, an image signal binarized by the error diffusion method is used as an image signal for recording / display.

Next, in step S106, character recognition is performed on characters cut out from each recognition line. Next, in step S107, the recognized character is converted into font data. Next, in step S108, the font data and the image data other than the recognition line (the image binarized by the binarization processing unit using the error diffusion method) are synthesized. Therefore, in FIG. 1, the image data conversion unit 110 expands the font data from the recognized character obtained by the recognition control unit 111 when the target line is a recognition line, and also, when the target line is image data, the image buffer memory. From 118, the binarization unit 12
The image signals binarized by the error diffusion method at 0 are respectively switched and output to the image editing unit 107.

Next, details of the process in step S106 will be described with reference to FIG.

FIG. 8 shows step S10 of FIG. 4 of the present embodiment.
6 is a flowchart illustrating details of a process 6;

A specific example of FIG. 8 will be described with reference to FIG. FIG. 9 particularly shows a recognition row (simple binarized image signal) obtained by further enlarging the top row of FIG.

First, in step S 200, the vertical direction (Y)
A histogram 550 is created by projecting black pixels in the direction. Next, in step S201, the left end of the first character of the recognition line is detected from the created histogram 550.
In this case, a pixel column 551 having a predetermined number or more of black pixels from the left end of the recognition row is detected.

In step S202, it is determined whether there is a black pixel in the column of the average character width H from the leading end of the character Cn. If there is a black pixel (YES in step S202), it is determined in step S204 that the character Cn is a half-width character. On the other hand, when there is no black pixel (NO in step S202), it is determined that the character Cn is a double-byte character.

The determination in step S202 is performed as follows. That is, since a normal kanji has an aspect ratio of about 1: 1, the average full-width character width H (=
V + α α is a constant). The number of black pixels 553 on the column 552 located to the right of the average full-width character width H from the pixel column 551
To evaluate. That is, if the character C1 is a double-byte character, no black pixel exists because the column 552 is located in the gap with the next character. Therefore, the number of black pixels in a column located on the right side of each character in the recognition row from the left end thereof to each average full-width character width H is evaluated to determine whether or not the character is a full-width character. Row 5
At 52, since no black pixel exists, the character C1 is determined to be full-width. On the other hand, the next character C2 similarly evaluates a black dot on the column 554 located at the average full-width character width H from the left end. In this case, since a black dot clearly exists on the column 554, it can be determined that the character C2 is not a full-width character.
In particular, in the present embodiment, the character C2 is determined to be a half-width because the character is identified as either a full-width or a half-width.

Next, in step S211, each area where the font of the character is identified as either full-width or half-width,
The presence of a character pixel in the full-width H * G and half-width (H / 2) * G areas is determined. If there is a character pixel (YES in step S211), the process advances to step S205 to perform recognition of the character Cn according to the size of the recognized character. On the other hand, if there is no character pixel (step S
In step S213, the process proceeds to step S213, where an image signal binarized by an error diffusion method capable of expressing halftones using characters as image data is selected.

In step S206, it is determined whether or not the character Cn can be recognized. If recognizable (YES in step S206), in step S207, the recognized character is developed into font data and replaced with new image data. On the other hand, if recognition is not possible (NO in step S206), the flow advances to step S212 to select an image signal obtained by simply binarizing characters as image data.

Next, in step S208, the leading end of the next character in the recognition line is detected. In step S209, it is determined whether the end of the recognition line has been reached. If the processing has not been completed (NO in step S209), the process returns to step S202. On the other hand, if the processing has ended (YES in step S209), the processing ends.

For example, FIG. 10 is an enlarged view of the image area separation result of the corresponding line. Obviously, for the characters C1 to C10 in FIG. Can be Therefore, in this case, recognition of each character is performed by normalizing the image data (simple binary signal) in the area for one character and comparing it with the recognition dictionary. On the other hand, a picture exists at the rear end of this row. That is, several character pixels 563 exist at the rear end portions A30 to A34 in FIG. 10 even if the isolation determination pixels are removed. Therefore, when the number of such character pixels is equal to or less than a predetermined value, the area of the one character sentence is a non-character part,
That is, an image signal binarized by an error diffusion method capable of expressing a halftone as image data is selected. It should be noted that when the above-described processing in step S202 is performed on the pixel 562 that is a simple binarized image signal shown in FIG. If the density of the image is light, it is determined to be full-width. In this case, the determination result for either full-width or half-width may be either.

Here, an example of the recognition method in step S205 will be described with reference to FIG.

FIG. 12 is a diagram for explaining an example of a recognition method according to the present embodiment.

FIG. 12 shows an example using a tree-structured recognition dictionary for recognizing a cut-out character [king].

Here, if the standard pattern vector (feature amount) of the i-th group in one stage in the tree-structured recognition dictionary is * vi and the input vector of the extracted character is * u, the vector * vi The distance from the vector * u is r
Is the number of dimensions of the vector,

[0070]

(Equation 1) It is represented by Then, along this tree structure, the shortest distance between the standard pattern of each group and the extracted character is determined in each of a plurality of stages that are formed by grouping similar standard patterns before and after. Ask. In this way, a down search is performed while forming a path connecting the groups giving the shortest distance, and the shortest distance character candidate (standard pattern) obtained in the final stage is output as a recognition character. In this way, the group with the smallest distance in each row is selected, and the character [King] in the last row shown in FIG.
Is formed.

When the distance between the obtained standard pattern vector as a character candidate and the input vector of the extracted character exceeds a certain value, the character candidate is not adopted, and it is determined that the character cannot be recognized. , And the extracted characters are treated as simple binarized image data. On the other hand, if it is recognized, the font data corresponding to the extracted character is replaced with a new image signal according to a procedure described later,
The left end of the next character in the recognition line is detected from the histogram 550.

Next, a method of converting recognized characters into font data will be described with reference to FIGS. 10, 11, and 13. FIG.

FIG. 10 shows a simple binarized image signal.
1 is an example of an image signal whose image area has been separated, and FIG. 13 is an example of a result obtained by converting a recognition result into font data according to the present invention.

FIG. 13 shows characters C1 to C10 extracted from the recognition line shown in FIG.
This is an example converted as 10. For the sake of explanation, the font is round Gothic and the font size is slightly smaller. The font data is developed by arranging the font data corresponding to the points 560 and 561 at the upper left corner of each cut character. Therefore, if the image is developed in a size larger than the character size of the document, the space between adjacent characters is reduced, and if the size is larger, the characters overlap.

It is assumed that the recognized character C6 cannot be recognized. In this case, as described above, the extracted character C6 is treated as image data and expanded into font data. The character B1 is combined with the character B10. Also, the rear end portions C30 and C3 of the row
1, C32, and C33 are combined with a binary image signal 564 by the error diffusion method. By aligning the end of the expanded font data with the end of the cut-out character in the recognition line in this way, even if the unrecognizable character is directly used as image data and synthesized into the font data, A high-quality image signal can be output as a document.

As described above, according to the present embodiment, if a character in a cut-out region can be recognized in a recognition line in which a character pixel exists, the character line is developed into corresponding font data. Further, even if the characters in the cut-out area are not recognizable, the presence of characters in the area is identified by the image area separation processing, and the unrecognizable character is converted into a simple binary image having the highest resolution. By selecting and outputting a signal, an image with good resolution can be generated.
Further, the picture part existing in a part of the recognition line is selected and output by selecting an image signal binarized by an error diffusion method capable of expressing a halftone based on the processing result of the image area separation processing, An image having a good gradation expression can be generated.

In the above embodiment, the row L1 shown in FIG.
3. Characters existing over the line L14 are recognized as normal characters, but are treated as unrecognizable characters because the shortest distance between the standard pattern and the extracted character exceeds a predetermined value. Then, it is clear that a character existing over the line L13 and the line L14 becomes an unrecognizable character in the processing shown in FIG. Therefore, step S in FIG.
In addition to evaluating the character pixels in the area cut out in the process of 211, that is, the area of H * G for full-width and (H / 2) * G for half-width, it particularly evaluates the character pixels in the horizontal direction (for example, line L13). (Step S214 in FIG. 14) is performed to determine whether or not a character pixel exists on the boundary between the line and the line L14). If the character is determined as an unrecognizable character and the process branches to step S212, the determination of the unrecognizable character can be performed more quickly.

The image area separating method for separating a character area in an image is not limited to the above embodiment. For example, another method using the number of binarized dots in an image, a density gradient, a density histogram, or the like is used. It can also be implemented using.

When the input document is a color document,
If a luminance signal is generated from the three color signals obtained by color separation, it is possible to recognize a character area in the same manner as a monochrome image signal.

Although the image area in the image is output as an image signal binarized by an error diffusion method, halftones can be expressed well. For example, multi-value pseudo halftone processing, tissue dithering, pulse width modulation May be output as a multi-valued image signal. In particular, when outputting as a multi-valued signal, the font data is output as 1-bit data of 0 and 1, for example, as 8-bit data of 0 and 255, and the unrecognizable character is a multi-valued signal obtained when an original image is read. If a halftone picture portion is subjected to a smoothing process on a multi-level signal obtained when a document image is read and then output, a higher quality image can be output. Can be

If character recognition is performed on a character area obtained as a result of image area separation without performing character recognition from a simple binarized image signal, and other blank parts are processed as image areas, Since the image area can be directly determined and the character recognition processing only for the character area needs to be executed,
Processing can be accelerated.

Although the isolation determination pixel is removed, the erroneous determination of a character pixel occurring in other pixels may be caused, for example, in an image area separation process for each area cut out from the recognition line. The determination may be corrected for the isolated recognizable character area that is sandwiched between the areas as a non-character area. For example, the area A31 in FIG. 10 is determined to be a character based on the number of character pixels, and character recognition is performed.
In this case, the corresponding character is not found in the character recognition result, and is eventually determined to be an unrecognizable character. As a result, FIG.
The image signal from which the simple binarized image signal of C31 of FIG. 1 is output, that is, the image signal of B31 in FIG. 13 is selected, and the generated image becomes extremely difficult to see. Therefore, A30 adjacent to A31 in FIG.
If A32 is determined to be a non-character area, A30,
A31 sandwiched between A32 also corrects the determination as a non-character area.

Even if the present invention is applied to a system composed of a plurality of devices (for example, a host computer, an interface device, a reader, a printer, and the like), a device including one device (for example, a copying machine, a facsimile machine) Etc.).

Further, an object of the present invention is to provide a storage medium storing a program code of software for realizing the functions of the above-described embodiments to a system or an apparatus, and a computer (or CPU) of the system or the apparatus.
And MPU) read and execute the program code stored in the storage medium.

In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiment, and the storage medium storing the program code constitutes the present invention.

Examples of a storage medium for supplying the program code include a floppy disk, hard disk, optical disk, magneto-optical disk, CD-ROM, and CD.
-R, a magnetic tape, a nonvolatile memory card, a ROM, or the like can be used.

When the computer executes the readout program code, not only the functions of the above-described embodiment are realized, but also the OS (Operating System) running on the computer based on the instruction of the program code. ) May perform some or all of the actual processing, and the processing may realize the functions of the above-described embodiments.

Further, after the program code read from the storage medium is written into a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, based on the instruction of the program code, It goes without saying that the CPU included in the function expansion board or the function expansion unit performs part or all of the actual processing, and the processing realizes the functions of the above-described embodiments.

When the present invention is applied to the storage medium, the storage medium stores program codes corresponding to the flowcharts shown in FIGS. 4, 8, and 14 described above.

[0090]

As described above, according to the present invention,
It is possible to provide an image processing apparatus and method capable of reproducing an image in which a character image and a halftone image are mixed with higher quality, and a computer-readable memory.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a functional configuration of an image processing apparatus according to an embodiment.

FIG. 2 is a cross-sectional view illustrating a hardware configuration of the image processing apparatus according to the embodiment.

FIG. 3 is a diagram illustrating an appearance of an operation unit according to the embodiment.

FIG. 4 is a flowchart illustrating a processing flow of an image recognition unit according to the embodiment.

FIG. 5 is a diagram illustrating an example of an image and a histogram creation result according to the embodiment;

FIG. 6 is a diagram illustrating an example of a determination result of a recognition row according to the embodiment;

FIG. 7 is a diagram illustrating details of a histogram creation result according to the present embodiment.

FIG. 8 is a flowchart illustrating details of a process in step S106 in FIG. 4 of the present embodiment.

FIG. 9 is a diagram for explaining processing performed on a recognition row according to the embodiment;

FIG. 10 is a diagram illustrating an example of a recognition method according to the embodiment.

FIG. 11 is a diagram for explaining a method of converting to font data according to the present embodiment.

FIG. 12 is a diagram illustrating an example of a recognition method according to the embodiment.

FIG. 13 is a diagram for explaining a method of converting to font data according to the present embodiment.

FIG. 14 is a flowchart illustrating another example of the processing flow of the image recognition unit of the present embodiment.

[Explanation of symbols]

 Reference Signs List 101 lens 102 image sensor 103 AD converter 104 shading correction circuit 105 mode switching circuit 106 light density conversion circuit 107 image editing unit 108 character cutout unit 109 vector calculation unit 110 image data conversion unit 111 recognition control unit 113 CPU 114 ROM 115 RAM 116 Operation unit 117 Recording unit 118 Image buffer memory 119 Image area separation unit 120 Binarization unit 1001 Document 1002 Image reading unit 1003 Image processing unit 1004 Image recording unit 4000 Image recognition unit

Continuation of the front page (72) Inventor Junnosuke Kataoka 3-30-2 Shimomaruko, Ota-ku, Tokyo Inside Canon Inc. (72) Inventor Makoto Kobayashi 3-30-2 Shimomaruko, Ota-ku, Tokyo Inside Canon Inc. (72) Inventor Eiwa Honda 3-30-2 Shimomaruko, Ota-ku, Tokyo F-term in Canon Inc. (reference) 5B029 AA01 BB02 CC21 CC29 DD03 EE11 5B064 AA01 BA01 CA03 CA08 DC17 5C077 MP01 NN11 PP27 TT06

Claims (19)

[Claims] 1. An image processing apparatus for processing an input image, comprising: extracting means for extracting a character line in the input image; and cutting out an area image from the character line extracted by the extracting means. Output means; character recognition means for character recognizing an area cut out by the extraction means; first generation means for generating a first image signal corresponding to the character recognized by the character recognition means; Means for generating a second image signal for an area image in which characters cannot be recognized by the means; third generating means for generating a third image signal for an image other than the character line in the image; and the first image An image processing apparatus comprising: an output unit that synthesizes and outputs a signal, the second image signal, and the third image signal. 2. The image processing apparatus according to claim 1, wherein the first image signal is font data corresponding to the character. 3. The image processing apparatus according to claim 1, wherein the second image signal is a simple binarized image signal. 4. The image processing apparatus according to claim 1, wherein the third image signal is an image signal subjected to pseudo halftone processing. 5. The character recognizing means includes first determining means for determining whether or not a pixel exists at a boundary of a character line adjacent to the attention area image, and based on a determination result of the first determining means. 2. The image processing apparatus according to claim 1, wherein the target area image is determined to be a non-character recognizable area image. 6. The character recognition means includes a second determination means for determining whether or not the attention area image is character recognizable, based on the number of pixels present in the attention area image, The image processing apparatus according to claim 1, further comprising: determining the target area image as an area image in which characters cannot be recognized based on a determination result of a determination unit. 7. The apparatus according to claim 1, wherein the character recognizing means determines that the region of interest image is a region image incapable of character recognition when a region image adjacent to the region of interest image is not character recognizable. Image processing device. 8. The image processing apparatus according to claim 1, wherein when the image is a multi-level image signal, the second image signal is an edge-emphasized multi-level image signal. 9. The image processing apparatus according to claim 1, wherein when the image is a multi-valued image signal, the third image signal is a smoothed multi-valued image signal. 10. An image processing method for processing an input image, comprising: an extraction step of extracting a character line in the input image; and an area image cutting out an area image from the character line extracted in the extraction step. An output step; a character recognition step of recognizing a character in the area cut out in the extraction step; a first generation step of generating a first image signal corresponding to the character recognized in the character recognition step; A second generation step of generating a second image signal for an area image in which characters cannot be recognized in the step; a third generation step of generating a third image signal for an image other than the character line in the image; and the first image An output step of combining and outputting a signal, the second image signal, and the third image signal. 11. The apparatus according to claim 10, wherein the first image signal is font data corresponding to the character.
The image processing method according to 1. 12. The image processing method according to claim 10, wherein the second image signal is a simple binarized image signal. 13. The image processing method according to claim 10, wherein the third image signal is an image signal subjected to pseudo halftone processing. 14. The character recognition step includes a first determination step of determining whether or not a pixel exists at a boundary of a character line adjacent to the attention area image, and based on a determination result of the first determination step. 11. The image processing method according to claim 10, wherein the attention area image is determined to be an area image in which characters cannot be recognized. 15. The character recognition step includes a second determination step of determining whether or not the attention area image is capable of character recognition based on the number of pixels present in the attention area image; The image processing method according to claim 10, further comprising: determining the attention area image as an area image in which characters cannot be recognized based on a determination result of the determination step. 16. The character recognition step according to claim 10, wherein, if an area image adjacent to the attention area image is not capable of character recognition, the attention area image is determined to be an area image incapable of character recognition. Image processing method. 17. When the image is a multi-valued image signal,
The image processing method according to claim 10, wherein the second image signal is a multi-valued image signal with edge enhancement. 18. When the image is a multi-valued image signal,
The image processing method according to claim 10, wherein the third image signal is a smoothed multi-valued image signal. 19. A computer-readable memory storing an image processing program code for processing an input image, wherein: a program code for an extraction step for extracting a character line in the input image; A program code of a cutting step of cutting out an area image from the character line extracted in the above, a program code of a character recognizing step of recognizing a character in the area cut out in the cutting step, and A program code of a first generation step of generating a corresponding first image signal; a program code of a second generation step of generating a second image signal for an area image in which characters cannot be recognized in the character recognition step; A program code of a third generation step of generating a third image signal for an image other than the character line, the first image signal, the second image signal, Image signal, a computer readable memory; and a program code of the third image signal combining and outputs the output process.