JPH0799535B2 - Character figure recognition method - Google Patents

Description

The present invention relates to a character / figure recognition system for recognizing character / figure on a medium.

(Prior Art) Conventionally, a character / graphics recognition apparatus has often adopted a method of extracting strokes from a character / graphics pattern and recognizing them by using the positions, lengths, mutual relationships between the strokes, and the like of the extracted strokes. There is. The method is as follows: (1) The curvature is calculated for the contour point series detected by tracing the contour of the character figure, the contour series is divided with the point having a large curvature value as the division point, and the divided series is combined. Strokes are extracted by combining them, or (2) the character / graphic pattern is thinned to form a skeleton, the connectivity of the skeleton pattern and the skeleton pattern are traced, and a sudden angle change point is detected to make a stroke. And extract (1) and (2) above
The strokes thus extracted are identified by extracting geometrical features and the like.

In addition, as a method of easy processing, (3) a range defined by a character frame with respect to a black bit number distribution on two predetermined axes (for example, a horizontal axis and a vertical axis) obtained by scanning an input character / graphic pattern Determine the barycentric coordinates with. Then, in the respective barycentric coordinates detected so far, the process of determining the barycentric coordinates of each of the black bit number distributions for each range obtained by dividing the range defined by the character frame is repeated a plurality of times. Find the series. The input character / graphic pattern is divided in the respective axial directions by the divided coordinate series which is substantially evenly associated with the obtained respective barycentric coordinate series, and the respective divided area lengths on the respective axes are divided into the respective axes. The normalized divided area length sequence obtained by normalizing with the character frame length in the direction is extracted as a feature of the input character / graphic pattern and identified.

(Problems to be Solved by the Invention) However, the conventional character / graphics recognition method has the following problems.

In the method (1), if the character / graphic pattern becomes large and the character / graphic pattern becomes complicated, the processing amount increases and the processing speed decreases. In the method (2), it is necessary to make the character / graphic pattern thin, and there are problems such as pattern distortion and beard due to the thinning, and the subsequent processing is complicated. Although the method of (3) is simple in processing, since the character / graphic pattern originally having a two-dimensional property is expressed by a feature representing a one-dimensional property such as a divided region length, the input character / graphic pattern is used. In that case, it was difficult to identify.

SUMMARY OF THE INVENTION It is an object of the present invention to solve the above-mentioned problems and to provide a character / figure recognition system capable of recognizing a character / figure quickly and accurately by a simple process.

(Means for Solving Problems) In order to solve the above problems, the present invention reads a character graphic on a medium, quantizes it, and binarizes it. For example, a character line part is a black bit and a background part is white. In a character / figure recognition system for recognizing a character / figure based on the pattern, comprising: a storage unit for storing a pattern obtained as a bit; (a) a first pattern for scanning the pattern to detect a circumscribing frame of the character / figure; (B) scanning the pattern on two predetermined axes (for example, a horizontal direction and a vertical direction in a two-dimensional coordinate).
Hereinafter, these are referred to as X axis and Y axis. ) To create a black bit number distribution in each axial direction projected onto the image), (c) determining the barycentric coordinates of each black bit number distribution within the range of the circumscribing frame in the two axial directions, and determining each barycenter. Second detection means for detecting the barycentric coordinate series in each axial direction by repeating the process of determining the barycentric coordinates of each black bit number distribution for each divided range obtained by dividing the range in the circumscribed frame by coordinates, (d) setting Determining means for determining a division coordinate series in each axial direction corresponding to the centroid coordinate series based on the number of divisions, (e) for each division area in the circumscribing frame divided by the division coordinate series, Calculation means for calculating a divided area area matrix in which the area of the divided area is normalized by the area in the circumscribing frame, and (f) the divided area area matrix is collated with the previously calculated divided area area matrix of the standard pattern. Character diagram of the pattern Those having a recognition means for recognizing.

(Operation) According to the present invention, since the character recognition system is configured as described above, the technical means operates as follows. By scanning the pattern stored in the storage means, the circumscribing frame (character frame) of the character graphic is detected by the first detecting means, and the creating means detects the circumscribing frame in each axial direction (for example, X-axis, Y-axis direction). A black bit number distribution is created. Based on the circumscribing frame and black bit number distribution thus obtained, the barycentric coordinate series in each axial direction is detected by the second detecting means. Next, based on the set number of divisions, the determining unit determines the dividing coordinate series in each axial direction corresponding to the barycentric coordinate series detected by the second detecting unit. The number of divisions is set, for example, according to the complexity of the character graphic. A matrix of divided area areas (divided area area matrix) is calculated for each divided area in the circumscribing frame that is divided by the divided coordinate series obtained by the determining means, and the area of the divided area is normalized by the area in the circumscribing frame. Calculated by means. The normalized divided area area matrix and the divided area area matrix of the standard pattern calculated in advance in the same manner are collated by the recognizing means, and the category name of the corresponding standard pattern is output as the character graphic name. As described above, according to the present invention, by using the center of gravity of the black bit number distribution obtained by scanning the pattern of the character graphic, the divided area area matrix expressing the two-dimensional property is obtained as the characteristic information of the character graphic, and this characteristic information is obtained. Since the character / graphics are recognized by using, it is possible to recognize the character / graphics quickly and accurately by a simple process.

(Embodiment) An embodiment of the present invention will be described below with reference to FIGS. 1 to 5.

FIG. 1 is a functional block diagram showing a character / graphics recognition apparatus to which the system of the present invention is applied. The character recognition device of this embodiment is
A photoelectric conversion unit 2 for photoelectrically converting the light input 1, a pattern register 3, a character frame detection unit 4, a character projection creation unit 5, a center of gravity detection unit 6, a character frame division point determination unit 7, a normalized division area area calculation unit 8, It comprises an identification unit 9, a dictionary memory 10 and an output terminal 11.

An optical input 1 from a medium such as a form in which characters, figures, symbols and the like (hereinafter referred to as characters) are written is input to a photoelectric conversion unit 2. The photoelectric conversion unit 2 photoelectrically converts the optical input 1 to decompose one character planned area into 128 × 128 pixels, and each pixel is a binary digital signal (hereinafter referred to as an input character pattern).
Is converted to, and one character of average size is 60 × 60
It is expressed by an input character pattern of about bits. The pattern register 3 stores the input character pattern in a format capable of reproducing the X and Y coordinates of each pixel in the character planned area, and has a capacity of 128 × 128 bits corresponding to the character planned area.

The character frame detection unit 4, for example, defines a circumscribing frame (character frame) of a character as the left end coordinate X _l , the right end coordinate X _r ,
The upper limit coordinate Y _t and the lower limit coordinate Y _b are used for detection.

The character projection creating unit 5 projects the input character pattern of the pattern register 3 on a predetermined axis, for example, the X axis and the Y axis (horizontal direction and vertical direction in the two-dimensional coordinates of the husband and wife pattern register 3) to distribute the number of black bits. , The black bit number distribution SX
Create (x) and SY (y).

Here, x and y are two-dimensional coordinates 0 to 127 in the pattern register 3, Y _t and Y _b are upper and lower coordinates in the Y axis direction of the character frame, and X _l and X _r are X axis directions. Is the left and right coordinates of P, and P (x, y) means black bit or white bit. In case of black bit (significant color), in case of P (x, y) = 1, white bit (background color) Take P (x, y) = 0.

FIG. 2 (a) shows an example of input character patterns in the case of the patterns of Chinese characters “Ta” and “Kuchi”, and FIG. 2 (b), (c)
The black bit number distribution SX for each pattern in Fig. 2 (a)
(X) and SY (y) are shown.

The center-of-gravity detection unit 6 determines the entire range X _{l to} X _r , in the X and Y axis directions of the character frame.
Y _t ~ Y _b and its range X _l ~ in the barycentric coordinates detected in the previous process
Targeting each range obtained by dividing X _r , Y _{t to} Y _b , the barycentric coordinate series X (M _p ), Y (M _q of the black bit number distributions SX (x) and SY (y) of the input character patterns ) Is obtained by dividing the sum of the first moments in each range by the black bit sum in that range. However, M _p and M _q are barycentric coordinate numbers given in order of magnitude of coordinate values, and M _p = 1
~ MX (MX is the number of centers of gravity in the X-axis direction) M _q = 1 to MY (MY is Y
The number of center of gravity in the axial direction). As the number MX of the barycentric coordinates in the X-axis direction, it is desirable to use a relatively large number (about the number of divisions) of about 15, but for the sake of simplification of explanation, 7 barycentric coordinates X (M _The case of detecting _p ) will be described.

First, for the range X _{l to} X _r in the X-axis direction of the character frame, the black bit number distribution SX of the input character pattern is calculated as shown in the following equation.
The center of gravity coordinate X (4) of the center of gravity coordinate number 4 is obtained by dividing the first moment sum of (x) by the black bit sum in the range. Then, the divided respective ranges that center coordinates _{X (4), X l ~X} (4), 2 two barycentric coordinates as a target of X4~X _r X (2), determining the X (6).

Next, the barycentric coordinates X (2), X detected so far
Range X _{l to} X (2), X (2) divided by (4), X (6)
~X (4), X (4 ) ~X (6), X (6) 4 pieces of the center of gravity to X _r as object coordinates X (1), X (3 ), X (5), X (7) Ask for.

If the number of barycentric coordinates MY that also detects the barycentric coordinate Y (M _q ) in the Y-axis direction is set to 7, first, the black bit number distribution SY of the input character pattern is targeted for the range Y _{t to} Y _b of the character frame. (Y)
Of detecting the center coordinates Y (4), then the range Y _t ~Y (4) for 2 minutes character frame center of gravity coordinates, Y (4) ~Y _b black bits number distribution as a target each SY of (y) Barycentric coordinates Y (2), Y
(6) is detected, and the barycentric coordinate Y detected so far
(2), Y (4) , Y (6) range and each divided character frame in the Y-axis direction by _{Y t ~Y (2), Y} (2) ~Y (4), Y (4) ~
Black bit number distribution SY for Y (6), Y (6) to Y _b
By detecting the barycentric coordinates of (y), a total of seven barycentric coordinates Y (1) to Y (7) are detected.

In the case of the input character patterns of the Chinese characters “Ta” and “Kuchi” (FIG. 2 (a)), the black bit number distributions (SX (x), SY (y) in FIGS. 2 (b) and (c) are shown. ) Center of gravity X
(1) to X (7) and Y (1) to Y (7) are shown.

The character frame division point determination unit 7 receives the X, Y received from the center of gravity detection unit 6.
The barycentric coordinate series X (M _p ), Y (M _q ) in each direction of the axis is used as a divisional coordinate candidate, and the barycentric coordinate numbers M _p and M _q are substantially evenly associated with the divisional coordinate numbers k _i and k _j. NX, N in the character frame of the pattern
Division coordinate series DX (k
_i ), DY (k _j ) are determined.

The division format of the division unit area in this embodiment can take four formats as NX = 4,5,6,8 as the division number in the X-axis direction, and similarly, the division number NY in the Y-axis direction is NY.
= 4,5,6,8, and the divided coordinate numbers in the X-axis direction are k _i (k _i = 1 to NX-1, NX = 4,5,6,8) and Y The division coordinate numbers in the axial direction are k _j (k _j = 1 to NY-1, NY = 4,5,
6, 8), the division coordinate series DX (k _i ) and DY (k _j ) that divide the character frame into the number of division unit areas NX · NY are determined. The divided coordinate series D by associating the barycentric coordinate numbers M _p and M _q in the X and Y axis directions with the divided coordinate numbers k _i and k _j in the X and Y axis directions almost equally
Table 1 shows the table used to determine X (k _i ) and DY (k _j ).

Referring to this table, X, division number NX of Y-axis in each direction, the centroid coordinate number M _p from the table in response to NY, reads the M _q, centroid corresponding to the barycentric coordinate number M _p, M _q Coordinate X
(M _p ) and Y (M _q ) are determined as the division coordinates DX (k _i ) and DY (k _j ).

The table in Table 1 shows a case where the number of barycentric coordinates MX and MY detected by the barycentric detecting unit 6 is 7, but in a general case, the barycentric coordinates of the number of divisions in each of the X and Y directions are included. It is possible to make it by making correspondence so as to include one more barycentric coordinate in order from the regions at both ends when extra barycentric coordinates remain.

In Fig. 3, NX = NY = as the number of divisions NX, NY in each direction of the X and Y axes.
When a division number of 5 is specified, the division coordinate series
The correspondence between DX (k _i ), DY (k _j ) and the barycentric coordinate series X (M _p ), Y (M _q ) is shown, and their divided coordinate series DX
(K _i), indicating the DY divided unit areas set in _{(k j) (k i,} k j).

The number of divisions NX, NY is N depending on the complexity of the input characters.
It decides X, NY, or changes the number of divisions NX, NY when it is rejected, and makes character recognition again.

As described above, in the character frame division point determination unit 7, the division format of the division unit area is NX = 4,5,6, as the number of divisions in the X-axis direction.
8 formats, the number of divisions in the Y-axis direction is NY = 4,5,
It can take four formats: 6,8. In this embodiment, the number of divisions will be described below with NX = NY = 8. In this case, in the X-axis direction, divided coordinates DX (1) to DX (7) corresponding to the barycentric coordinates X (1) to X (7), and in the Y-axis direction, the barycentric coordinates Y (1) to Y ( Division coordinates DY (1) corresponding to 7)
~ Determine DY (7).

The normalized divided area area calculation unit 8 determines the character frame coordinates X _l , X _{r in} the X direction and the character frame coordinates Y _t , Y _{b in} the Y axis detected by the character frame detection unit 4, and the character frame division point determination. Divided coordinates in the X-axis direction determined by unit 7 DX (1) to DX (7) Divided coordinates in the Y-axis direction
Received DY (1) to DY (7), the area of each divided area divided by each divided coordinate on each axis is normalized by the product of the lengths between the both end coordinates, and the normalized divided area area matrix Is calculated by the following equation (6).

Normalized divided area area matrix; Length between coordinates on both ends of X axis; LX = X _r −X _l + 1 ……… (7) Length between coordinates on both ends of Y axis; LY ＝ Y _b −Y _t +1 ……… (8) However, DX (0) = X _l , DX (8) = X _r , DX (0) = Y _t ,
DY (8) = Y _b . K is a constant, and K = 1000 in this embodiment.

Figure 4 shows the division coordinates DX (0) to DX (8) and DY (0) to DY.
(8) and the normalized divided area area matrix {BES (I, J) | I
= 1 to 8 and J = 1 to 8}. Further, in FIG. 2 (a) described above, the division coordinates DX (0) to DX (8), DY in the input character pattern of the Chinese characters “Ta” and “Kuchi” are input.
(0) to DY (8) and the division coordinates of the input character pattern (in the character frame) are divided into respective areas.

Normalized divided area area matrix f _i as the characteristic information of the input character pattern obtained by the normalized divided area area calculation unit 8
= {BES (I, J) | I = 1 to 8, J = 1 to 8} is given to the identification unit 9.

In the dictionary memory 10, the normalized divided area area matrix g _i as the characteristic information for the standard pattern calculated in the same manner as the case of the input character pattern is registered in advance.

The identification unit 9 measures the similarity between the characteristic information of the input character pattern obtained as described above and the characteristic information of the standard pattern, recognizes the character code of the most similar standard pattern as the input character graphic pattern name, and recognizes the character code. Is output to the output terminal 11. In the present embodiment, the weighted Euclidean distance of the following equation (9) between the normalized divided area area matrix g _i of the standard pattern in the dictionary memory 10 and the normalized divided area area matrix f _i of the input character pattern ( The standard pattern that gives the minimum value of D) is the most similar standard pattern.

Here, the weight of the Euclidean distance (D) is the weight coefficient W _i given to each divided area, and in the present embodiment, the weight coefficient is
Set W _i to all 1.

Further, in the above-described embodiment, the barycentric coordinates and the divided coordinates are associated with each other by using the table, but they can be associated with each other by executing the flow chart arithmetic processing of a predetermined procedure. . The flow chart in this case is shown in FIG.

All the results of the division in FIG. 5 are rounded down to the right of the decimal point.

In Figure 5, obtains a divided ivy number M _alpha gravity number MX by dividing the number NX at step S1, step S2, S3 obtains the quotient R ₂ obtained by dividing the remainder R ₁ and its R ₁ of MX / NX at 2 . Further, the number of divisions calculated median k _alpha in step S4, the excisional division number k _i and the center of gravity number M _p to 0 in step S5, S6. Also, steps S7, S8, S9
Every time the division number k _i is incremented by 1, the set quotient R ₂ is decremented by 1 and the center of gravity number M _p is incremented by M _α . Check that the quotient R ₂ in step S10 is not negative, one increases the number of centroid numbers at step S11 as long as the quotient R ₂ is not negative,
At step S12, the center of gravity number M _{p is associated} with the division number k _i , and the division coordinate DX (M _p ) is determined. If the quotient R ₂ is negative, it is determined in system S13 whether the current division number k _i is larger than the median k _α. If it is larger, the center of gravity number is incremented by 1, and if it is smaller, it is set in step S9. The centroid number is used to determine the division coordinate DX (M _p ), and in step S14 the division number k _i becomes (NX-
Detects that it matches 1) and terminates.

The effectiveness of the normalized divided area area matrix, which is the characteristic information of the character / graphics recognition method of the present embodiment described above, will be described below.

For example, in the input character patterns of "Ta" and "Mouth" respectively shown in FIG. 2 (a), the phase difference between the vertical stroke and the horizontal stroke at the center of the pattern is a normalized divided area area matrix. 1) BES (5,4), a characteristic difference appears, and it is clear that the normalized divided area area matrix effectively reflects the difference in the character / graphic pattern. In this example, the same applies to BES (4,4), BES (4,5), and BES (5,5).

In addition, the feature of the normalized divided area area matrix reflects the density of the character line in the divided area and its area in the X-axis direction and the Y-axis direction in each divided area divided by using the barycentric coordinate series. Represents the two-dimensional nature of the original graphic pattern. Therefore, compared with the one represented by the one-dimensional characteristic of the original character graphic pattern which originally has the two-dimensional characteristic, such as the feature of the normalized divided area length sequence shown in the method (3) of the prior art, The feature of the normalized divided area area matrix used in the present embodiment is a safe feature, and the present embodiment enables more stable recognition of character graphics.

Further, since the characteristic of the normalized divided area area matrix is that each divided area is normalized by the area inside the character frame that expresses the size of the character, it is stable even against variations in the size of the character. .

As described above, according to the present embodiment, since the normalized divided area area matrix, which is obtained by scanning the input character pattern and the predetermined calculation and represents a two-dimensional property, is used as the character feature information, a simple process is performed. Thus, it is possible to recognize a character (including a figure, a symbol, etc.) at high speed, accurately, and stably with respect to a variation in the size of the character figure.

(Effects of the Invention) As described in detail above, according to the present invention, an input character / graphic pattern can be obtained without performing complicated pattern processing such as contour tracing or thinning in the characteristic information extraction of the conventional character / graphic recognition method. By using the barycentric coordinate series obtained from the black bit number distributions on the predetermined two axes obtained only by scanning, the normalized divided area area matrix that is the characteristic information representing the two-dimensional property is obtained, and this is obtained as a character. Since it is used for figure recognition, it is possible to examine the minute differences in the shape of the character by simple processing and accurately, and while it is stable against changes in the size of the character figure, it is possible to check the character figure. it can.

[Brief description of drawings]

FIG. 1 is a functional block diagram showing an embodiment of a character / figure recognition system according to the present invention, and FIGS. 2 (a), (b), and (c) are examples of input character patterns, a barycentric coordinate series, and a divided coordinate series. FIG. 3, FIG. 3 is a diagram showing a correspondence relationship between the barycentric coordinate series and the division coordinate series, FIG. 4 is a view showing a correspondence relationship between the division coordinate series and the normalized divided area area matrix, and FIG. Is a flow chart showing another method of determining the divided coordinate series. 1 ... Optical input, 2 ... Photoelectric conversion unit, 3 ... Pattern register, 4 ... Character frame detection unit, 5 ... Character projection creation unit, 6
...... Center of gravity detection unit, 7 ...... Character frame division point determination unit, 8 ...... Normalized division area area calculation unit, 9 ...... Identification unit, 10 ...... Dictionary memory, 11 ...... Output terminal

Front page continuation (72) Inventor Koji Ito 1-7-12 Toranomon, Minato-ku, Tokyo Oki Electric Industry Co., Ltd. (56) Reference JP-A-58-123171 (JP, A) JP-A-61-150086 (JP, A)

Claims (1)

[Claims] 1. A character / figure recognition system that includes a storage unit for storing a pattern obtained by reading and quantizing a character / figure on a medium, and recognizing a character / figure based on the pattern, comprising: (a) scanning the pattern. First detecting means for detecting the circumscribing frame of the character figure, (b) creating means for creating a black bit number distribution in each axis direction by scanning the pattern and projecting it on two predetermined axes, (c) The barycentric coordinates of each black bit number distribution are determined within the range of the circumscribing frame in the two axial directions, and the range of the black bit number distribution is divided into each of the divided ranges obtained by dividing the range within the circumscribing frame by the determined barycentric coordinates. Second detection means for detecting the barycentric coordinate series in each axial direction by repeating the process of determining the barycentric coordinates, (d) based on the set division number, the divided coordinates in each axial direction corresponding to the barycentric coordinate series Determining means for determining the series, (E) For each of the divided areas in the circumscribing frame divided by the division coordinate series, a calculation means for calculating a divided area area matrix in which the area of the divided area is normalized by the area in the circumscribing frame, (f) A character / figure recognition system, comprising: a recognition means for recognizing a character / figure of the pattern by comparing the divided area area matrix with a previously calculated standard area of the divided area area matrix.