JPH0370629B2 - - Google Patents

Description

[Detailed description of the invention]

[Technical Field of the Invention] The present invention relates to a compression method for character/image (hereinafter referred to as character) data, and in particular, a method for approximating the outline of a character with a function curve or a set of straight lines and storing information specifying the outline. The present invention relates to a method for processing character image data, in which the amount of data is compressed by a method, and the compressed data is decoded to reproduce a character image. [Background of the Invention] It is well known that binary data obtained by dividing characters into dots has extremely high redundancy. Therefore, various data compression methods have been proposed to reduce this redundancy. One such data compression method is the so-called contour method, which compresses the amount of data by determining the shape of a character by its outline and storing information specifying the outline. As data compression methods using the contour method, a straight line (vector) approximation method as shown in FIG. 1 and an n-th order curve approximation method as shown in FIG. 2 have already been proposed. The straight line approximation method illustrated in Figure 1 is
This is a method disclosed in Japanese Patent Publication No. 149522, Japanese Patent Application Laid-open No. 1979-79154, etc., and its outline is that the contour 1 of an arbitrary character indicated by a dotted line is expressed as a two-dimensional vector 2 indicated by a straight line.
It is possible to compress data by approximating a set of vectors and storing specific information (starting point position, length and slope, or horizontal and vertical components) of each vector as stored data. Furthermore, the n-th curve approximation method illustrated in FIG.
This is a method that has already been applied for as a patent application (No.), and its outline is to compress the amount of data by storing the coordinates of a group of points P appropriately set on the outline of an arbitrary character, and to store arbitrary consecutive (n+1) points. Connect the points of n
This is a set of curved elements 3 that attempt to approximate a desired contour. These contour method-based data compression methods are said to be able to cope with character image reproduction at various magnifications by performing interpolation processing or vector magnification conversion processing when decoding the compressed data and reproducing character images. It has characteristics. [Problems with background technology] However, on the other hand, these conventional methods, for example,
The end point P of each vector in FIG. 1, or
The smoothness of the contour ( This method has an essential flaw in that it does not guarantee optimal results regarding the continuity of the slope of the contour. On the other hand, in general, the outline shape of a character is not only continuous, but also the shape of the outline itself is not only continuous, but also unique points such as the intersection of the character strokes and the tips of the "springs" are excluded. In this case, the first derivative (the slope of the contour) has a characteristic that it changes continuously. Therefore, with the conventional data compression method using the contour method, it is not only difficult to obtain compressed data that is faithful to the character contour, but also it is difficult to accurately remove unnaturalness (discontinuity in slope) of the character image reproduced based on the data. The problem was that I couldn't do it. In order to solve these problems, the applicant has already applied for the method of Japanese Patent Application No. 16884-1984 (Japanese Patent Application No. 134745-1982). However, the data compression method disclosed here attempts to approximate the entire contour at once;
In contour areas where straight lines and curved lines are continuous,
At the connection point, unevenness that deviates from the contour is likely to occur. In addition, if we try to avoid these problems, we will have to set more sample points and perform approximation by dividing into many polynomials, which obviously leads to an increase in the amount of compressed data. Summer. Furthermore, since complex calculations are required to obtain the compressed storage data, there remains the problem that it takes time to create the storage data. [Object of the Invention] An object of the invention is to provide an improved contour method data compression method, and another object of the invention is to reduce the calculation time when calculating compressed data. Nevertheless, it is an object of the present invention to provide a method for processing character image data that can obtain compressed data that is faithful to character contours. The object of the present invention is to provide a method for processing character image data that can obtain a sufficiently high data compression rate.
Furthermore, another object of the present invention is to decode compressed data according to the present invention to reproduce a character image.
To provide a method for processing character image data that can faithfully reproduce character images of various magnifications having smooth contours. [Summary of the Invention] An overview of data processing related to the method of the present invention will be explained according to the flowchart shown in FIG. The input character image is dot-decomposed into a [x,y] matrix (30), and the outline of the dot-decomposed character image is extracted (31). The extracted contour is linearly approximated by a vector whose deviation from the contour is less than the allowable error (32). The contour approximated by a straight line is
The vectors are distinguished into straight and curved parts based on their lengths (33), and on the other hand, dividing points of the contour are determined by determining the intersection angles of adjacent vectors (34).
Then, for a straight section, the contour shape of the section is expressed by an n-degree polynomial (n=1), and for a curved section, the contour shape of the section is expressed by an n-degree polynomial (n=2,
3) Approximate the curve. To approximate the curve,
The slope at each contour point forming the contour is determined (35), and an n-th degree polynomial is determined from the coordinates of both ends of the section to be approximated by the curve and its slope. Then, while extending the interval, find the longest interval (sample interval) within the range where the deviation between the n-th degree polynomial that approximates the interval and the contour is within the allowable error, and find both end points of the interval. This will be determined as a sample point (36). In this way, sample intervals are sequentially determined, and when an n-degree polynomial that approximates each sample interval is determined, the first derivative of each n-degree polynomial is determined, and the slope of each contour point is calculated again (37). Then, sample points are determined in the same manner as described above based on the newly obtained slope and coordinate values of each contour point, and an n-th degree polynomial that is more faithful to the contour is calculated (38). Coding the coefficients, degrees, etc. of the n-dimensional polynomial thus obtained (39),
Furthermore, in order to efficiently restore the character outline later,
Each block data is stored in the order of the distance between the starting point and the ending point in the x direction of one block (40). The stored compressed character contour data is then distributed and decoded by a plurality of decoders (41), and a desired character contour is restored based on the decoding results (42). [Embodiments of the Invention] Next, data processing in each part will be explained in detail. [Image input (30)] Characters/images are separated into dots in a [x, y] matrix by raster scanning using a scanner device, etc., and the bit pattern data obtained thereby is the original character data to be processed. Supplied as. [Contour extraction (31)] The binary data corresponding to the decomposed dot changes from "0" to "1" or "1" in the x or y direction.
The contour can be obtained by finding the dot position (contour point) that changes from "0" to "0". Then, the obtained contour is divided into blocks of a monovalent function with x as a variable to form a set of multiple blocks. Figure 4 shows a contour extracted from character data dot-decomposed into an [x, y] matrix, and the contour is divided into monovalent function blocks (intervals from "〇" to "〇"). It is. [Line approximation (32)] Linear approximation is performed for any one block on the contour using a large number of vectors set as long as possible within a range where the amount of deviation from the contour is within a predetermined tolerance. FIG. 5 shows a linear approximation of a character outline 50 shown by a dotted line using a set of two-dimensional vectors 51 in an arbitrary block [P ₁ , P _o ].
Connection points of each vector 51 P ₁ , P ₂ , ..., P _o-1 , P _o
are stored as sample points in the sample point coordinate storage unit 6, which will be described later.
Store as 0. [Identification of straight and curved parts of a character outline (33)] As mentioned above, the outline shape of a character generally has a straight part and a curved part, and in the past, the entire outline was identified at once. Therefore, for contours where straight and curved parts are continuous, many sample points must be set near the connection points, and the process must be divided into many approximation formulas. This has resulted in a disadvantage that the amount increases and the compression ratio decreases. Therefore, the present invention identifies whether the contour shape is a straight part or a curved part based on the length of the vector obtained by the linear approximation described above, and processes the straight part and the curved part separately. I tried to eliminate the shortcomings. FIG. 6 is a block diagram showing an embodiment of a configuration that realizes a method for identifying straight and curved portions of a character outline. In the figure, 60 is a sample point coordinate storage unit that stores the sample points obtained by the linear approximation (32) in units of blocks, 61 is a straight line section identification vector length setting unit that sets the identification vector length L, and 62 is a A curve dividing point identification angle setting unit sets the curve dividing point identification angle θ, and 63 is the next sample point coordinate for holding the coordinates (x _l+1 , y _l+1 ) of the i+1th sample point P _l+ 1 Register 64 is the coordinates of the i-th sample point P _l (x _l + y _l )
, 65 is a previous sample point coordinate register for holding the coordinates (x l-1 , y l-1 ) of the i-1th sample point P _l-1 , and 66 is a previous sample point coordinate register for holding the coordinates (x _l-1 , y _l-1 ) of the i-1th sample point P l-1 . A vector length calculation unit that calculates the vector length l _l of the sample interval [x _l , x _l+1 ] from each coordinate of the next sample point coordinate register 63 and the current sample point coordinate register 64; 67 is the next sample point coordinate register 63, a vector-to-vector angle calculation unit that calculates the vector-to-vector angle θ _l at the sample point P _l from the coordinates of the current sample point coordinate register 64 and the previous sample point coordinate register 65; 68, a straight-line portion identification vector length setting unit 61; Discrimination vector length L set by
and the vector length l calculated by the vector length calculation unit ₆₆ , and 69 is a curve division point identification angle θ set by the curve division point identification angle setting unit 62 and the vector-to-vector angle calculation unit. 67
Angle comparison sections 70 and 71 compare the vector-to-vector angle θ _l calculated in , and 70 and 71 are linear section storage sections and curved section sections that respectively store the sections of the straight section or the curved section based on the comparison result of the vector length comparison section 68. Memory section, 72
is calculated in the angle comparing section 69 when θ>θ _l
This is a curve division point coordinate storage unit that stores the th sample point P _l as a curve division point. Next, the operation will be explained. First, the straight line section identification vector length setting section 61 sets the identification vector length L.
The curve dividing point identifying angle θ is set in the curve dividing point identifying angle setting unit 62, respectively. Next, the starting point coordinates of any one block are sent from the sample point coordinate storage section 60 to the next sample point coordinate register 63. At this point, nothing is stored in the current reference point register 64, so the vector length cannot be determined by the vector length calculation unit 66, which will be described later. Next, the sample point coordinates stored in the next sample point coordinate register 63 are stored in the current sample point coordinate register 64, and the next sample point coordinates are newly stored in the next sample point coordinate register 63. Thereafter, the sample point coordinates of the current sample point coordinate register 64 are shifted and stored in the previous sample point coordinate register 65, and the sample point coordinates of the next sample point coordinate register 63 are shifted and stored in the current sample point coordinate register 64. The coordinate register 63 stores the next sample point coordinate from the sample point coordinate storage section 60. The vector length calculation unit 66 calculates the coordinates (x _l+1 , y _l+1 ) of the i+1st sample point P _l+ 1 in the next sample point coordinate register 63 and the i-th sample point in the current sample point coordinate register 64. From the coordinates (x _l , y _l ) of P _l , the vector length l _l
Calculate =√( _l − _l+1 ) ² + ( _l − _l+1 ) ² . The calculated vector length l _l is compared in a vector length comparison section 68 with the discrimination length L preset by the straight line section discrimination vector length setting section 61. Here, when l _l > L,
The section [x _l , x _l+1 ] is determined to be a straight section, and the starting point coordinates and end point coordinates of the section are stored in the straight section storage section 70 . When l _l ≦L, the section [x _l , x _l+1 ] is determined to be a curved section, the section is temporarily stored, and the next section is identified. Here, if the next section is a straight line section, the stored section [x _l , x _l+1 ] is treated as a curve section, and its starting point coordinates and end point coordinates are stored in the curve section storage section 71 . On the other hand, if the next section is also a curved section, the next section is further identified, and when the section to be identified changes from a curved section to a straight section, the continuous section of the curved section up to that point is divided into one continuous section. As a curved part, its starting point coordinates and ending point coordinates are stored in the curved part storage unit 7.
Store in 1. [Divide contour (34)] On the other hand, in the inter-vector angle calculation unit 67, the next sample point coordinate register 63 and the current sample point coordinate register 6
4. From the previous sample point coordinate register 65, the coordinates (x _{l-1 ,} y _{l -1 )} , (x _l ,
y _l ), (x _l+1 , y _l+1 ) are read out, and the intervector angle θ _l (θ _l is an acute angle) shown in FIG. 5 is calculated. The calculated inter-vector angle θ _l is compared in an angle comparison section 69 with a curve division point identification angle θ set in advance by the curve division point identification angle setting section 62 . Here, when θ>θ _l , the sample point P _l is newly set as a curve dividing point, and its coordinates are stored in the curve dividing point coordinate storage section 72. Normally, there are many sample points near this curve dividing point, and it takes time to process the obtained approximate curve, but by dividing the contour at the curve dividing point obtained above, it is possible to Since each curve is approximated separately, the processing time is quick and the approximated curve can be easily obtained. FIG. 7 shows an example in which the above-described data processing of [linear approximation (32)] to [contour division (34)] is performed on the character contour data shown in FIG. 4. In the figure, 〇 is the starting point and ending point of one block,
△ is a sample point obtained by linear approximation, and ● is a curve dividing point. Also, * indicates a straight part, and no mark indicates a curved part. [Calculating the slope of each contour point (35)] When approximating the contour shape of the curved portion obtained above using an n-dimensional polynomial (where n = 1, 2, 3),
The n-th degree polynomial is uniquely determined once the coordinate values and inclinations of the two points are determined. Therefore, in this case, it is first necessary to find the slope at each contour point on the contour. In the present invention, the slope at each contour point is determined by extracting a predetermined number of contour points before and after the contour point, and determining the slope of a line segment connecting the contour point whose slope is to be calculated and each extracted contour point. The slope at a desired contour point is calculated. A method of calculating the slope at each contour point according to the present invention will be explained with reference to FIG. First, as shown in Figure 8a, the slope at the starting point P ₁ (contour point Q ₁ ) of any one block [P ₁ , P _o ] on the contour
To find t ₁ , extract an arbitrary number of contour points that exist after the starting point P ₁ , calculate the slope of the line segment connecting the starting point P ₁ and each contour point, and calculate the slope t at the starting point P ₁ from each slope. ₁ is calculated using the formula described below. For example, if two contour points are extracted and the slope is determined, first the slope m ₁ of the line segment _{1 2} and the slope m ₂ of the line segment _{1 3} are calculated. The slope m ₁ of a line segment is the coordinates of two points (x ₁ , y ₁ ), (x ₂ ,
m ₁ = y ₂ −y ₁ /x ₂ −x ₁ from y ₂ ). In addition, in the case of _m2 , it is found in the same way. When the slopes m ₁ and m ₂ of the line segments are determined, the contour point Q ₁
The slope t ₁ at is determined by t ₁ =tan (tan ^-1 m ₁ +tan ^-1 m ₂ /2). Note that the end point can also be determined in the same manner. Next, when calculating the slope t ₂ at the next contour point Q ₂ as shown in Fig. 8b, extract a predetermined number of contour points before and after _{the contour point Q 2 ,} and calculate Find the slope of each line segment connecting the lines, and find the slope _t2 at the contour point _Q2 . For example, when determining the slope by extracting the two contour points, only the front one point can be extracted at the contour point _Q2 , so in this case, by extracting the two points before and after the contour point Q2, the slope _t2 is calculated from the following equation. t ₂ = tan (tan ^-1 m ₁ + tan ^-1 m ₂ /2) If the specified number of contour points does not exist, the maximum number of contour points within the specified range will be extracted to calculate the slope. Make it. Next, when calculating the slope _t3 at the contour point _Q3 as shown in FIG. 8c, the predetermined number of contour points exist before and after the contour point _Q3 . contour point
The slope of each line segment connecting Q ₃ and each contour point is m ₁ , m ₂ ,
Find m ₃ and m ₄ respectively, and calculate the slope t ₃ at contour point Q ₃ as t ₃ = tan (tan ^-1 m ₁ + tan ^-1 m ₂ + tan ^-1 m ₃ +
tan ^-1 m ₄ /4). Then, the slope at each contour point is calculated in the same manner as the contour points are successively selected. [Determination of sample points (38)] Once the slope at each contour point is determined as described above, the approximate curve determined by the two contour points on the contour is determined, and the amount of deviation between the approximate curve and the contour is determined. is calculated for each contour point one by one. If each deviation in the approximation curve section in question is less than the allowable error, the contour point is advanced one more time and the same process is repeated again, so that the deviation is within the allowable error. The contour is divided into sample sections while determining the longest section (hereinafter referred to as a sample section). Then, the contour is approximated by an n-dimensional polynomial determined by this sample interval. Hereinafter, the calculation method of the approximate curve of the n-th degree polynomial and the calculation method of the amount of deviation will be explained using FIG. 9. First, the straight part storage section 70 and the curved part storage section 71
Based on the coordinate values stored in , it is determined whether the approximated section is a straight section or a curved section. If the section is a straight section, the starting point coordinates of the section and a linear equation (linear equation) indicating the section are calculated and encoded as described later. Next, a case where the section is a curved section will be explained. In FIG. 9a, S _l (Q ₁ ) is the starting point of the i-th sample section of interest, and the starting point S _l
(Q ₁ ) and sample candidate point S _l+1 (Qn) are set as a sample candidate section, and approximate curves are sequentially determined.
B is the contour point Q _j , C is a straight line that is perpendicular to the straight line 92 connecting the sections to which the curve is approximated and passes through point B (Q _j )
The intersection of BQ93 and approximate curve 91 is the contour point
The amount of deviation in the x direction between the contour 90 and the approximate curve 91 at Q _j is the amount of deviation between the contour 90 and the approximate curve 91
is the amount of deviation between the contour 90 and the approximate curve 91 in the y direction. Also, the interval [Q ₁ ,
Since the n-th polynomial in Q ₂ ] is uniquely determined to be a straight line, an approximate curve of the n-th polynomial is found from the next interval [Q ₁ , Q ₃ ]. Hereinafter, the case of a cubic curve will be explained as an example. The slope of the already calculated starting point S _j (Q ₁ ) and sample candidate point Q _o
By substituting t _l , t _o and the coordinate values (x _l , y _t ), (x _o , y _o ) into the cubic equation below, the approximate curve f(x) of the section is obtained.
is found. f(x)=y _l +b _l (x-x _l ) +c _l (x-x _l ) ² +d _l (x-x _l ) ³ b _l =t _l c _l =3(y _o -y _i )/ x _o −x _i −2t _i −t _o /x _o −x _i d _l =t _i +t _o −2(y _o −y _i )/x _o −x _i /(x _o −x _i ) ² or more Once each coefficient that determines the approximate curve f(x) is determined, the amount of deviation ε between the approximate curve f(x) and the contour is determined. The offset position ε is obtained at each contour point Q _j (where 2≦j≦n−1) existing in the section. In the figure, when determining the deviation amount ε (=) between the contour 90 and the approximate curve 91, in the present invention, the deviation amount ε
is calculated in a pseudo manner, allowing for faster processing. FIG. 9b shows the contour 90 and the approximate curve 9 at a.
This is an enlarged version of the difference from 1. In the figure, it is assumed that the line segment is parallel to the straight line 92,
Let the slope m of the line segment be the slope of the straight line 92. Then, by determining the distances ε _x and ε _y from the approximate curve 91 in the x and y directions at the contour point B (Q _j ), the desired deviation amount ε is obtained as follows:

[Formula] (When |m|>1)

[Recalculating the slope of each contour point (37)]

As described above, when a contour is approximated by a cubic approximate curve in each of a plurality of sample sections, the coordinates of the starting point of the sample section and the order and coefficients of the approximate curve that approximates the sample section are stored as contour data. A compressed code can be obtained by doing this. However, the slope of each contour point obtained in the above [calculation of slope of each contour point (35)] is the average value of the slopes of a predetermined number of contour points before and after it,
The actual slope may differ greatly. Therefore, in the present invention, in order to approximate the contour more faithfully, the first derivative f'(x) of the approximate curve f(x) in each sample section is obtained, and the slope at each contour point in the sample section is calculated again. I decided to do so. [Re-determination of sample points (38)] Based on the inclination and coordinate values of each contour point obtained through data processing in the above-mentioned [Recalculation of slope of each contour point (37)], the above-mentioned [Determination of sample points (36)] ]
In the same manner as above, determine the sample interval while determining the sample points again. The sample points obtained in this manner are approximated by an approximate curve f(x) that is more faithful to the contour in the sample section. [Coding (39)] In the above manner, the starting point coordinates of each sample section in the straight and curved sections obtained, the coefficients and orders of the approximate curve f(x), etc. are encoded, and further organized into blocks. By storing the data as a set of block data, it is possible to obtain compressed data that is faithful to the outline of an arbitrary character. FIG. 10 is a diagram showing an example of a preferable data storage format for any one block data applied in implementing the present invention as described above. In the format shown in the figure, the block header stores the end coordinates of one block and the number of sample sections existing in one block, and the segment header stores the X, Y coordinates of the starting point of one sample section and the approximate curve f(x). The degree is stored, and the segment information stores each coefficient of the approximate curve f(x) determined by the degree. One sample section data is organized by the segment header and segment information, and further, sample section data according to the number of sample sections are arranged in sequence, and the whole constitutes one block data. . [Storage of compressed data (40)] Each block of data encoded in the above format is stored in units of blocks, which require a long decoding process time, in order to efficiently restore the character contours described later. Memorize in order. For example, FIG. 11a shows the case where compressed data is obtained for each block (for the sake of explanation, each block is numbered 1 to 20) for the character "A". Then, the blocks that take the longest time to decode (for example, the blocks that have the longest distance between the start and end points of each block in the x direction) are stored in order. In Figure 11a, the time required to decode one block is the longest for block 12, and the following block 1
0, block 16, and so on, with block 3 being the shortest. Therefore, the character outline compressed data finally obtained will be stored as a set of block data as shown in FIG. 11b. [Distributed Decoding (41)] What has been described so far relates to data compression of character contours. Next, a method for restoring the original contour based on the contour data compressed by the data processing method described above will be explained. In this case, in order to restore the contour quickly,
The block data for each block is sequentially transferred to a plurality of decoders for processing, and the next block data is processed from the decoder that has been processed. Therefore, the time required to decode one block as described above becomes a problem. In other words, the longer the time required to decode one block, the longer the processing time required to restore the contour. Therefore, when block data that takes a long time to process comes later, only that decoder continues processing while all other decoders finish processing, resulting in a decrease in decoder usage efficiency. Therefore, as mentioned above, the present invention stores the compressed data in the order of the time required to decode one block, and processes it with multiple decoders, so that the decoders can be used efficiently and the contour can be restored at high speed. did. This will be explained below with reference to FIGS. 12 and 13. FIG. 12 is a block diagram showing an embodiment for optimally performing contour restoration according to the present invention. In the figure, 120 indicates each block data as 1
A compressed data storage section 121 stores blocks in order of the time required for decoding the blocks, selector 1 selects and transfers one block of data to a decoder to be described later, 122 a magnification storage section 123 stores a desired magnification input separately. 124 is a decoder group consisting of n decoders that restores the block data to a contour corresponding to a magnification, and 124 is a decoder group of the decoder group 123,
The selector 2, 125 selects the decoder that has completed the processing and transfers the contour pixel data obtained by decoding to the single character storage section described later.
The single-character storage section 126 that stores the contour data sent from the single-character storage section 125 is an output device that prints or displays characters based on the contour pixel data for one character that has been stored in the single-character storage section 125. Next, the operation will be explained. From the compressed data storage unit 120, the blocks are stored in the order of the time required to decode one block (for example, in FIG. 11, block 12, block 10, block 16
...) to selectors 1 and 121. Selectors 1 and 121 select decoders in order from decoder 1 of decoder group 122 to transfer the transferred block data. After the transfer of the block data is completed, the decoder starts contour restoration processing based on the block data and desired magnification data separately stored in the magnification storage section 122. The selectors 2 and 124 sequentially select the decoders that have completed the restoration process, and transfer the restored contour pixel data to the one-character storage unit 125. The decoder that has completed the restoration process for one block requests the selector 1, 121 to transfer the block data, and the next block data is transferred. FIG. 13 shows each decoder group 12 shown in FIG.
3 is a timing chart showing an example of processing state No. 3; In the figure, T ₁ is the time to transfer block data from selector 1, 121 to each decoder, and T ₂
is the time required to transfer the contour pixel data decoded by each decoder to the one-character storage unit 125 via the selectors 2 and 124, and _T3 is the decoding processing time of block data in each decoder. Further, _T4 indicates the processing time for one character. When n blocks of block data are transferred to decoders 1 to n and processing starts, the next (n+1)th block data is transferred to the decoder with the shortest processing time (in this case, decoder 3) and continues processing. I'll keep going. Moreover, since each block of data to be transferred is arranged in the order of decreasing processing time as described above, each decoder finishes processing for one character almost simultaneously, as shown in Figure 13. . Therefore, each decoder operates almost equally, and the decoding of character data is completed as quickly as possible without wasting idle time. [Contour Restoration (42)] As described above, one block of contour pixel data restored by each decoder is sequentially stored in the one character storage section 125, and one character's worth of contour pixel data is completed. Then, by supplying the outline pixel data for one character stored in the one-character storage unit 125 to an output device 126 such as a laser beam printer, CRT phototypesetting machine, display device, etc. The desired character is restored. [Effects of the Invention] As a result of applying the character image data processing method of the present invention described above to the Mincho hiragana character "a" consisting of 800 x 800 dots and testing, it was found that the desired character image was acceptable. If the error is 1 dot,
We were able to obtain a data compression rate of 1.21%. Further, in the above explanation, "a" has been explained as an example, but it is clear that images of various marks, symbols, line drawings, etc. other than kanji and letters can also be handled in the same way. As described above, according to the present invention, data that faithfully stores the smoothness of character contours can be obtained at high speed with a sufficiently high compression ratio, and furthermore, when restoring, high-quality character images can be reproduced at high speed at a desired magnification. A method for processing character image data can be provided.

[Brief explanation of drawings]

1 and 2 are diagrams explaining conventional contour method data compression, FIG. 3 is a flowchart showing an overview of data processing related to the method of the present invention, and FIG. A diagram showing an example of dividing the value function into blocks, Figure 5 is a diagram explaining linear approximation,
FIG. 6 is a block diagram showing an embodiment of the method for identifying straight and curved portions of the present invention, FIG. 7 is a diagram showing identification results by the identification method of the present invention, and FIG. 8 is a block diagram of each contour point according to the present invention. 9 is a diagram illustrating a method for determining a sample point according to the present invention. FIG. 10 is a diagram illustrating an example of a storage format of block data. FIG. 12 is a block diagram illustrating an embodiment of a configuration in which block data is restored according to the present invention.
FIG. 13 is a timing chart showing the operation of FIG. 12. 1, 50, 90... Character outline, 2, 51... Two-dimensional vector, 3... m-dimensional curve element, 60... Sample point coordinate storage section, 61... Straight line section identification vector length setting section,
62...Curve division point identification angle setting unit, 63...Next sample point coordinate register, 64...Current sample point coordinate register,
65... Previous sample point coordinate register, 66... Vector length calculation section, 67... Vector angle calculation section, 68... Vector length comparison section, 69... Angle comparison section, 70... Straight line section storage section, 71... Curved section storage section, 72... Curve division point coordinate storage unit, 91... Approximate curve of n-th degree polynomial, 1
20...Compressed data storage unit, 121...Selector 1,
122... Magnification storage unit, 123... Decoder group, 12
4...Selector 2, 125...1 character storage section, 126
...Output device.

Claims (1)

[Claims] 1. Encoded data for specifying the outline of a character image expanded on x, y coordinates is stored, and the encoded data is decoded to reproduce the original character image. In a method for processing character image data, the contour is divided into blocks of a monovalent function with x as a variable, a plurality of encoded block data specifying each block are obtained, and each block data is decoded. Each block is stored in order of the length of time required for each block to be retrieved, and
A method for processing character image data in which the block data successively generated in each block is distributed to a plurality of decoders in sequence and decoded as appropriate.