JP2782977B2 - Line figure vectorization method and apparatus - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method and an apparatus for vectorizing a line graphic obtained by quantization with an image scanner or the like, for example, raster data of various design drawings into vector data.

[0002]

2. Description of the Related Art Conventionally, there have been proposed various methods for converting a graphic into vector data approximated by a set of short lines by inputting a drawing input by an image scanner or the like.

A first method is a method of generating vector data by tracking a thinned image obtained by using a graphic thinning process. The thinning process is a process of repeatedly erasing a figure on a digital image by one pixel from surrounding black pixels until the line width becomes one pixel. Since a line image having a line width of 1 can easily be tracked, vector data can be obtained by performing approximation processing during tracking. For a typical algorithm for thinning, see “Thin
ing algorithms onrectangul
ar, hexagonal and triangu
lar arrays "(ES Deutsch,
C. ACM, vol. 15, no. 9,1972, p
p. 827-837).

[0004] As a second method, there is a method in which processing speed on software is emphasized, a contour of a figure is traced on a digital image, and then data obtained by approximating a short line segment of the contour image is used. In the short line segment data, the short vector pair is detected from the property that the short vector pair facing each other across the black pixel (graphic part) has a direction difference of about 180 °, and the midpoint position of the short vector pair is calculated. Thus, the center line of the figure is detected. In this case, an extremely large operation is required for the process of searching for a short vector pair opposite to the black pixel from the set of approximate short line segments of the outline, but the outline approximate short line data is managed by using a BD tree, and a round robin is obtained. There has been proposed a method of increasing the efficiency by avoiding the search by using. For details, see the document “Drawing processing using multidimensional data structure” (Osawa, Sakauchi, IEICE Transactions (D) J68
-D, No. 4).

As a third method, there has been reported a method of detecting a locus of a center point by moving a maximum arc that does not protrude from a black pixel region of a figure in the black pixel region of the figure. Although this method has high accuracy but extremely high calculation cost, a method of performing the same processing using a maximum rectangle instead of a maximum arc to reduce the calculation cost has been reported.

[0006]

According to the first conventional method as described above, raster scanning of an image must be repeated as many times as the number of layers of pixels to be erased. In order to perform processing in time, dedicated hardware is required, and the corners of the figure become dull due to the influence of the thinning distortion, and the structure of the sharp corner portion is not sufficiently preserved.

Further, the second method has a problem that the accuracy of searching for a pair vector based on an enormous outline approximating short vector is not sufficient. In other words, in a search using only the distance between the contour approximating short vectors and the mutual directional relationship as a clue, local irregularities of the contour greatly affect, and particularly in an image having a complicated structure, the pair vector cannot be detected. More often.

[0008] The third method, compared to the first and second methods,
High accuracy is obtained, but a very large amount of calculation is required. This is the same when the maximum circle is rectangular.

An object of the present invention is to solve the above-mentioned problem and to provide a line graphic vectorization method and apparatus for generating vector data with high precision while keeping the amount of calculation relatively small.

[0010]

According to the present invention, the boundary between white pixels and black pixels of binary raster data obtained by quantizing a line figure by an image scanner or the like is traced clockwise or clockwise in reverse. Regarding the extracted contour information, when an arbitrary contour pixel is set as a main point of interest and a contour pixel located at the shortest distance from the main point of interest across a figure is set as a sub-point of interest, the corresponding sub-pixel is moved while moving the main point of interest. In the line figure vectorization method of searching for a point of interest and detecting a curve connecting the middle point between the two points of interest as a core line, when the distance between the main point of interest and the sub-point of interest is within a predetermined value, the main point of interest is Moves in the data order of the contour information, and detects the two points of interest by moving the sub-points of interest in reverse order to the data arrangement of the contour information.If the distance between the two points of interest exceeds a predetermined value, , The position of the next main point of interest has been detected It estimated from the approximate polynomial of the core wire, and detecting a new primary point of interest on the basis of the estimation result.

The present invention also relates to contour information extracted by tracking all the boundaries between white pixels and black pixels in binary raster data obtained by quantizing a line figure by an image scanner or the like in a clockwise direction or in a reverse direction. When an arbitrary contour pixel is set as a main point of interest and a contour pixel located at the shortest distance across the figure from the main point of interest is set as a sub point of interest, a corresponding sub point of interest is searched while moving the main point of interest. , A song connecting the midpoint between the two points of interest
In a line graphic vectorization apparatus configured to detect a line as a core line , image input means for inputting an image to obtain binary raster data, image storage means for storing the raster data, Contour information detecting means for detecting information, contour information storage means for storing the detected contour information, and main point of interest extracting means for extracting main points of interest from the contour information at regular intervals in the data arrangement order of the contour information. In order to determine a sub-point of interest, data is taken out from the contour information storage means in the reverse order of the data arrangement of the contour information with the immediately preceding sub-point of interest as a starting point, and the distance between the two points of interest is calculated using a distance calculating means. Is compared with a predetermined threshold value, and the distance between the obtained sub-target point and the corresponding main target point is compared with a predetermined threshold value. The core wire Out and transferred to the unit, if exceeding a predetermined threshold value, the main and determining means moves the processing to the target point position estimation unit, a result according mainly focused point to estimate the primary target point from discovered core position of said determining means In accordance with the result of the estimating means, the determining means, there is provided a skeleton extracting means for extracting a midpoint between the two points of interest as a point on the skeleton, and a skeleton information storing means for storing detected skeleton information. .

[0012]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
This will be described with reference to the drawings. 2, 3 and 4 are views for explaining the operation of the present invention.

In the raster-vector conversion of the present invention, a method is used in which contour information obtained by tracking all contour black pixels in either clockwise or counterclockwise direction is used. The description will be made assuming that it has been performed. The contour information described here is array data in which the coordinate values of the contour pixels and the label values of the object to which the pixels belong are arranged in a line in the order detected by tracking. Also, two pixels on the contour forming the shortest distance across the black pixel are called a main point of interest and a sub point of interest. The two points of interest can be detected by sequentially searching for sub-points of interest corresponding to each main point of interest in the process of detecting main points of interest at regular intervals while tracing the contour. In this method, a method for efficiently performing the processing at this time will be described. If both points of interest can be detected, the skeleton data can be extracted by calculating the coordinates of the midpoint. Hereinafter, a processing method for a part where a branch point does not appear and a processing method for a part where a branch point exists will be described in order. (Centering at a portion without branch) The process of searching for a sub-point of interest is generally a process that requires a very high computational cost. However, for a portion without a branch structure, raster data is not directly referred to.
The search range is limited using the data arrangement order of the contour information,
Reduce computation costs. The main point of interest is detected by reading the contents of the array data of the outline information at regular intervals in the forward direction. The secondary point of interest detection is performed by reading coordinate value data within a certain range in reverse order from the immediately preceding secondary point of interest, calculating the distance to the corresponding primary point of interest, and detecting the data that takes the minimum value. Do.

FIG. 2 will be used to specifically show what data is extracted in the above processing. Here, {a} is a set of contour pixels, and takes a coordinate value a (x, y) as an element. In FIG. 2, the pixel indicated by the symbol ○ is a contour pixel, the pixel indicated by the symbol ● is a main point of interest in the contour pixel, and the pixel indicated by the symbol ◎ is a sub-point of interest.
The point indicated by the symbol x is a sequence of points indicating the detected center line passing position. a _i is the coordinate value of the main point of interest, and a _j is the coordinate value of the corresponding point of interest. In the outline information, a
_i is the i-th data and a _j is the j-th data. In the figure, the position of the main point of interest obtained by reading the contour information in the data arrangement order at a constant interval T (T = 4 in the figure) is a
_i , a _{i + T} and a _{i + 2T} . Here, the value of T is a value determined depending on the resolution of the input graphic and the image data. Set a value slightly longer than the average line width.

Data is read out at intervals of T in order from the i-th data of the contour information, and the coordinate values _ai , _{ai + T} , a
_{When i + 2T} is detected, the corresponding sub-points of interest are searched in the reverse order of the outline information data arrangement under the following conditions. <Search Condition> The k-th sub-point of interest from a _i is a point having the minimum distance d _k within the range represented by the following equation.

[0016]

(Equation 1)

[0017]

Here, the coordinate values of a _i and a _j are (x
_ai , _yai ) and ( _xaj , _yaj ),

(Equation 2)

[0019]

## EQU1 ## a _j-mk is m _k pieces back data from a _j contour information.

In a section where a structure such as a branch does not appear, that is, in FIG. 2, three sets of main points of interest and sub-points of interest are sequentially detected.

The dot sequence representing the core line is calculated by the following equation (3).

[0023]

(Equation 3)

[0024]

However, in FIG. 2, k = 0, 1, and 2.

According to the above-described method, the distance calculation (Equation 1) and the midpoint position calculation for a small number of candidates are performed by using the data arrangement order of the information (contour information) of the contour tracing result in the portion having no branch structure. Core line extraction is possible only with (Equation 3). (Centralization at Branched Part) Next, processing for a branched part will be described. When the value d _k of Equation 1 exceeds a predetermined threshold value D, an approximate curve is obtained from a series of points representing the core lines extracted so far, and the next search direction can be determined based on the approximate curve. It is. Thus, even if there is a branch structure, it is possible to continuously perform the core line extraction in a direction in which the extracted core lines are smoothly connected. This will be specifically described with reference to FIGS. 2, 3, and 4.

Now, it is assumed that a sequence of points f ₀ , f ₁ , f ₂ representing the core line has been extracted. If D is a threshold value empirically determined in advance, Equation 1 becomes

(Equation 4)

[0028]

If the condition is satisfied, it can be determined that the k-th middle point is approaching the branch point. In FIG. 2, when k = 3, it is assumed that Equation 4 is satisfied. The extracted point sequence f _k , k = {0,1,
2｝ approximation curve

(Equation 5)

[0030]

Is obtained by least squares approximation, and this is used as an estimated core line F (see FIG. 3).

Next, the point at which the approximate curve F intersects the contour pixel at the point beyond f ₂ is detected, the position of the detected contour pixel in the contour information data is determined, and according to the centering process at the part without branch,
2 points representing the core line

(Equation 6)

[0033]

Is calculated. This is a temporary core,
For verification, a line segment connecting these two points is regarded as a vector, and the following processing is performed.

On the estimated core line F in FIG.

(Equation 7)

[0036]

Take

(Equation 8)

[0038]

And extracted from the provisional main point of interest.

(Equation 9)

[0040]

It is checked whether or not the following conditional expression (Equation 10) is satisfied.

[0042]

(Equation 10)

[0043]

Here, θ _T is a threshold value of about 0.5. If the conditional expression (Equation 10) is not satisfied, the main point of interest and the sub point of interest are exchanged, a temporary main point of interest is moved to another nearby contour pixel, and a point satisfying the condition is searched. When the conditional expression is satisfied, the tentative main point of interest and the skeleton information are regarded as formal data, and the skeleton extraction processing is continued. In the example of FIG. 3, the core line pixel column can be detected as shown in FIG.

According to the above method, in a portion having no branching structure in a line figure, a core line can be extracted only by distance calculation for a small number of candidates using the data arrangement order of the contour information data obtained by the contour extraction processing. is there. Further, in the branch structure portion, line extraction can be performed in a direction that smoothly continues beyond the intersecting line segments. Therefore, it is possible to provide a line graphic vectorization method and a device thereof that are well-balanced in terms of processing speed and skeleton extraction accuracy, which are problems in the conventional method.

Next, an embodiment of a line graphic vectorization apparatus according to claim 2 will be described with reference to the drawings. FIG. 1 is a diagram showing an embodiment of a line graphic vectorizing apparatus.

This line graphic vectorizing device comprises image input means 1, image storage means 2, contour information detecting means 3, contour information storing means 4, main point of interest extracting means 5, sub point of interest detecting means 6, distance calculating means. 7, a determination unit 8, a main point of interest position estimation unit 9, a skeleton extraction unit 10, and a skeleton information storage unit 11.

The image input means 1 reads a line figure on a paper surface and converts it into binary raster data. Irradiate the paper with light,
The reflected light is photoelectrically converted by a one-dimensional CCD array element, and A / D
The digital data is obtained by conversion by a converter. The digital data is further binarized by an appropriate threshold value using a comparator or the like. The configuration is such that two-dimensional raster data can be obtained by mechanical scanning of the CCD array element. The obtained data is sent to the image storage means 2 and stored.

The image storage means 2 stores the binary raster data obtained by the image input means 1. The image storage means is constituted by a memory.

The contour information detecting means 3 reads the raster data from the image storing means 2, scans in the horizontal and vertical directions, and determines a black pixel at a position where a white pixel changes to a black pixel or a black pixel changes to a white pixel. The contour information is detected by tracking the black pixels clockwise or counterclockwise. Here, the outline information is a sequence of coordinate values of outline pixels labeled in object units. It can be constituted by a CPU, a program memory having the processing procedure shown in FIG. 5, a work memory, and the like. The processing procedure of FIG. 5 can be configured by a logic element. The contour information is written into the contour information storage means 4.

The contour information storage means 4 stores the contour information obtained by the contour information detecting means 3. The contour information storage means is constituted by a memory.

The main point of interest extraction means 5 extracts a main point of interest from the contour information. It has an access circuit to the contour information storage means 4, and has a function of detecting a main point of interest therein and outputting an address where the data is stored. The details of the processing are as described in the first embodiment. It is configured as a circuit mainly including a CPU, a program memory storing a processing procedure, and a work memory.

The sub-point-of-interest detection means 6 detects the contour pixel located at the closest distance from the main point-of-interest with respect to the figure. It has the function of receiving the data address of the main point of interest from the main point of interest detection means 5, referring to the coordinate data in the outline information based on this, and finding the sub point of interest. A data address at which the coordinate value of the pixel having the minimum distance is stored and a detection distance value are output. The details of the processing procedure are based on the first embodiment. It comprises a CPU, a program memory storing the above processing procedure, a work memory, and the like.

The distance calculating means 7 calculates the distance between the main point of interest and the sub point of interest. 2 to be compared from the secondary point of interest detection means 6
It has the function of receiving the coordinate values of one pixel, calculating the distance, and returning the value. It is composed of ALU and the like.

The judging means 8 compares the distance value between the sub-interest point obtained by the sub-interest point detecting means 6 and the corresponding main point of interest with a threshold value to judge whether or not the point is a correct corresponding point. .
It has a register for receiving and storing the distance value between the main point of interest and the sub point of interest from the sub point of interest detection means 6. Claim 1
A register for storing the threshold D value described in the embodiment, and a comparator for comparing the two register values, and the output of the comparator determines whether the main point-of-interest position estimating means 9 or the skeleton extracting means 10 performs processing. It has a control circuit for transferring. This is a necessary means for extracting a core line in a single continuous straight line direction without being affected even if there is an intersecting line segment.

The main point-of-interest position estimating means 9 is activated by the determining means 8 and has a function of accessing the main point-of-interest extracting means 5 to estimate the position of the next main point of interest. The detailed processing contents of this means are as described in the embodiment of claim 1, and comprise a CPU, a program memory storing the above processing procedure, a work memory, and the like.

The skeleton extracting means 10 is also started by the judging means 8 and calculates the coordinate value of a point through which the skeleton passes. This process calculates the midpoint between the main point of interest and the sub point of interest. The details are as described in claim 1. It comprises a register for storing coordinate values and an ALU.

The skeleton information storage means 11 is a skeleton extraction means 1
The memory is configured to store the core line information calculated at 0.

A system can be realized by the above configuration.

[0060]

According to the present invention, in a portion having no branching structure in a line figure, a core line is extracted only by distance calculation for a small number of candidates using the data arrangement order of the outline information data obtained by the outline extraction processing. Is possible. Further, in the branch structure portion, the core line can be extracted in a direction that smoothly continues beyond the intersecting line segments. Therefore, in terms of the processing cost and the core line extraction accuracy, which are problems in the conventional method, the accuracy is kept sufficiently high for practical use within the operation cost that can be sufficiently processed by software processing. A method and an apparatus thereof can be provided.

[Brief description of the drawings]

FIG. 1 is a functional block diagram showing an embodiment of a line graphic vectorization apparatus according to the present invention.

FIG. 2 is a diagram for explaining a line graphic vectorization method.

FIG. 3 is a diagram for explaining a line graphic vectorization method;

FIG. 4 is a diagram for explaining a line graphic vectorization method.

FIG. 5 is a flowchart illustrating a processing procedure of contour information detection.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Image input means 2 Image storage means 3 Contour information detection means 4 Contour information storage means 5 Primary attention point extraction means 6 Secondary attention point detection means 7 Distance calculation means 8 Judgment means 9 Primary attention point position estimation means 10 Core line extraction means 11 Core wire Information storage means

Claims (2)

(57) [Claims] An outline information obtained by tracing all the boundaries between white pixels and black pixels of a binary raster data obtained by quantizing a line figure by an image scanner or the like in a clockwise direction or in a reverse direction thereof, and extracting arbitrary information. When the contour pixel is set as the main point of interest and the contour pixel located at the shortest distance from the main point of interest across the figure is set as the sub point of interest, the corresponding sub point of interest is searched while moving the main point of interest, and both points of interest are searched. In the line graphic vectorization method for detecting a curve connecting the midpoints of points as a core line, when the distance between the main point of interest and the sub point of interest is within a predetermined value, the main point of interest is moved in the data arrangement order of the contour information. Then, the two points of interest are detected by moving the sub point of interest in the reverse order to the data arrangement of the contour information, and when the distance between the two points of interest exceeds a predetermined value, Estimate position from approximate polynomial of detected core Te, line drawing vectorization method characterized by detecting a new primary point of interest on the basis of the estimation result. 2. The method according to claim 1, wherein the boundary information of the binary raster data obtained by quantizing the line graphic with an image scanner or the like is traced all the clockwise or all in the opposite direction and extracted. When the contour pixel is set as the main point of interest and the contour pixel located at the shortest distance from the main point of interest across the figure is set as the sub point of interest, the corresponding sub point of interest is searched while moving the main point of interest, and both points of interest are searched. In a line graphic vectorization apparatus configured to detect a curve connecting the intermediate points of points as a core line, image input means for inputting an image to obtain binary raster data, and image storage means for storing the raster data Contour information detecting means for detecting contour information from the raster data; contour information storing means for storing the detected contour information; and extracting a main point of interest from the contour information at regular intervals in the data arrangement order of the contour information. A main point-of-interest extraction means, and to determine a corresponding sub-point of interest, extract data from the contour information storage means in the reverse order of the data arrangement of the contour information with the immediately preceding sub-point of interest as a starting point; A sub-point-of-interest detection means for detecting a point at which the distance between the two points of interest is the shortest, and comparing the distance between the obtained sub-point of interest and the corresponding main point of interest with a predetermined threshold value, If it is within the threshold value, the processing is shifted to the skeleton extracting means. If it exceeds the predetermined threshold value, the determining means shifts the processing to the main point of interest position estimating means. storing the main focus point position estimating means for estimating the main point of interest, according to the result of the determination means, wherein a centerline extraction means for extracting a midpoint between the two focused points as points on the core wire, the detected core information from Characterized by having a skeleton information storage means Graphic vector apparatus.