JP2823985B2 - Position data approximation method - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a position data approximating method for approximating position data of a point sequence using a function.

[0002]

2. Description of the Related Art In general, reading of shapes such as characters and figures with an image reader and reproducing them on a CRT or a paper sheet has been actively performed.

In this case, an outline font is called,
It has been practiced to read position data of only outlines of characters, figures, etc., and reproduce portions surrounded by the outlines as characters, figures, etc.

In the graphic processing using such an outline font, the outline of a character, a graphic, or the like is regarded as a dot sequence and read or reproduced. However, today, the position data of the original graphic is used as it is. Not
Approximate position data obtained by approximating this using an arbitrary function is used. This is because the position data of the original figure generally requires a large capacity when stored in a memory because of a large change, and a long time is required for various data processing and a long time is required for reproduction. By approximating this using, for example, an arbitrary function, the position data can be compressed, the storage capacity can be reduced, various data processing can be speeded up, and the reproduction time can be shortened. The reproduction figure can be reproduced.

Referring to FIG. 7, such a conventional approximation method will be described. First, in step ST11, an image is read using an image scanner or the like. Next, in step ST12, an outline of the image is extracted from the read image data. Next, step ST13
In the above, the section is divided in order to approximate the position data of the point sequence shape composed of the contour. Next, step ST
At 14, the position data of one divided approximate section is approximated using a predetermined function, and then, at step ST15, the approximate position data of the section is stored. Next, in step ST16, it is determined whether or not the approximation has been completed for all the divided approximation sections. If NO, the process returns to step ST14, and if YES, the approximation ends.

Using the approximate position data approximated in this manner, an image is reproduced by CRT or printing.

[0007]

However, in the above-mentioned conventional method, since the position data of the entire image is approximated by using one kind of function, the following inconvenience occurs. .

In other words, functions that approximate various types of position data include images that match the method of approximation using each function. For example, a cubic Bezier function is suitable for approximating an image in which the shape of a curve changes gradually, and a cubic spline function is suitable for approximating an image in which the shape of a curve changes little by little. ,
Different for each function.

Therefore, if the position data is approximated only by the cubic Bezier function, for example, if the approximation section is largely divided, the approximate position data which does not follow a fine change of the actual image is created. On the other hand, if the approximation section is divided into small sections in order to follow small changes in the actual image, the amount of approximation position data becomes very large, and the approximation operation requires a long time and a large capacity memory is required. There were inconveniences such as becoming. When approximation of position data is performed only by a cubic spline function,
There is a disadvantage that the concavities and convexities at the continuous points are increased more than necessary.

The present invention has been made in view of these points, and appropriately utilizes a plurality of functions to accurately approximate position data with a small amount of approximate position data, shortens the approximate calculation time, Further, it is another object of the present invention to provide a method of approximating position data in which the amount of memory can be reduced.

[0011]

In order to achieve the above object, a position data approximation method according to the present invention provides a method of approximating position data in a point sequence using a plurality of functions to obtain position data as approximate position data. In the approximation method, first, for each approximation target, if the approximate position data by an arbitrary function of the plurality of functions falls within a predetermined accuracy range, the approximation is performed using the function, and the approximate position When the data is out of the predetermined accuracy range, the data is approximated by using another function.

[0012]

According to the present invention, an approximation is first attempted for each approximation target using an arbitrary function, and when the approximate position data falls within a predetermined accuracy range, the approximation is performed using the function. If the data falls outside the specified accuracy range,
Since approximation by another function is performed, the position data can be accurately approximated with a small amount of approximate data by appropriately using a plurality of functions.

[0013]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to FIGS.

FIG. 1 is a flowchart showing an approximation method according to an embodiment of the present invention, which will be described below in order.

When approximating an image, first, in step ST21, the image is read using an image scanner or the like. Next, in step ST22, an outline of the image is extracted from the read image data. Next, in step ST23, a function to be used for approximation is selected from a plurality of functions. As the plurality of functions, a cubic Bezier function, a cubic spline function, a secondary Bezier function, a secondary spline function, or the like may be used, and the function used for the first approximation is selected from these functions. Next, in step ST24, the position data of the point sequence formed of the contour is approximated based on the selected function. Specifically, in order to approximate the position data of the point sequence shape composed of the outline, the section is divided according to the property of the selected function, and the position data of one divided approximate section is selected. Approximate using a function. In addition,
The division of the section may be performed between steps ST22 and ST23. Next, the process proceeds to step ST25, in which it is determined whether or not the approximate position data obtained in the previous step falls within a predetermined approximation accuracy range. If the approximate position data falls within the range of the predetermined approximate accuracy (YES), the process proceeds to step ST26, where the approximate position data is stored and stored in a memory (not shown).
Thereafter, in step ST27, it is determined whether or not the approximation process for the entire range, that is, the entire approximation section has been completed. If the approximation process has been completed, the approximation process is terminated. Then, the process returns to step ST23, and the approximation process for the next approximation section is performed in the same manner as described above.

If the result of determination in step ST25 is NO, which is that the approximate position data is out of the range of the predetermined approximation accuracy, the process proceeds to step ST28, and the degree of departure from the approximate range is selected in step ST23. It is determined whether or not the new function can be approximated by the same function as the new function. If the determination in step ST28 is YES, the process returns to step ST24 again, and the same approximation processing as described above is performed by newly increasing the section points in the approximate section. If the determination in step ST28 is NO, the process proceeds to step ST29.

In step ST29, it is determined whether or not there is another function used for approximation. If there is another function (YES), in the next step ST30, a function used for approximation is selected in the same manner as in step ST23. Next, in step ST31, an approximation process is performed using another selected function. Next, proceeding to step ST32, it is determined whether or not the approximate position data obtained in the previous step falls within a range of a predetermined approximate accuracy. YES that the approximate position data falls within the range of the predetermined approximate accuracy
In the case of, the process proceeds to step ST26, where the same approximate position data storage processing as described above is performed. In the case of NO,
Returning again to step 29, the same processing as described above is performed.

If the determination in step ST29 is NO based on the absence of another function, step S29
Proceeding to T33, from the approximate position data obtained in the approximate processing of steps ST29 to ST32, the approximate position data with the highest approximation accuracy is selected, and the selected approximate position data is stored in step ST26. Stored as approximate position data.

As described above, in the present embodiment, in steps ST23 to ST28, approximation processing is performed on each approximation target using the same function selected, and the approximation accuracy of the selected function falls within a predetermined value range. If not,
In steps ST29 to ST33, the approximation processing is performed using another function. Therefore, the position data can be accurately approximated with a small amount of approximate data by appropriately using a plurality of functions and the respective approximate features.

2 to 5 show another embodiment of the present invention.

In this embodiment, the first selected function is a cubic Bezier function, and the other functions are cubic spline functions.

FIG. 2 is a modification of the flowchart of FIG. 1 in order to perform an approximation process based on these two functions.

This embodiment will be described with reference to FIG. 2. First, in step ST41, an image is read using an image scanner or the like. Next, in step ST42, an outline of the image is extracted from the read image data. Next, in step ST43, the section is divided in order to approximate the position data of the point sequence formed of the contour. In this case, it is preferable that the number of approximation sections be a number sufficient to maintain a predetermined approximation accuracy when approximation is performed by a cubic Bezier function. Next, in step ST44, the position data of one of the divided approximate sections is approximated using a cubic Bezier function.

Next, proceeding to step ST45, it is determined whether or not the approximate position data obtained in the previous step falls within a predetermined approximation accuracy range. This determination is made as shown in FIGS.
That is, a sequence of points is reproduced based on the approximate position data obtained by the cubic Bezier function obtained in step ST44, and then, as shown in FIG. And a linear distance AB between the point A and the point B corresponding to the point A in the reproduced reproduction point sequence. If the value is within the allowable error range, YES is determined,
If it is outside the allowable error range, it is determined to be NO.

If the approximate position data falls within the range of the predetermined approximate accuracy (YES), the process proceeds to step ST46, and the approximate position data of the section is stored and stored in a memory (not shown). Next, in step ST47, it is determined whether or not the approximation has been completed for all of the divided approximation sections.
In the case of S, the approximation ends.

On the other hand, if the approximate position data is out of the range of the predetermined approximate accuracy and the answer is NO, the process proceeds to step ST48, in which the section is approximated based on a cubic spline function. The position data is stored in step ST46 as approximate position data of the section in the same manner as described above.

Since the approximation processing of this embodiment is performed in this manner, the reproduced figure approximated by only the third-order Bezier function shown in FIG. The reproduction figure based on the present embodiment shown in FIG. 7 has higher approximation accuracy with respect to the original figure of FIG. 6C, has a turnover, and is closer to the figure to be approximated.

FIG. 6 shows another embodiment of the present invention.

In this embodiment, the function selected first is a cubic spline function, and the other functions are cubic Bezier functions.

FIG. 6 is a modification of the flowchart of FIG. 1 in order to perform an approximation process based on these two functions.

This embodiment will be described with reference to FIG. 6. First, in step ST51, an image is read using an image scanner or the like. Next, in step ST52, an outline of the image is extracted from the read image data. Next, in step ST53, the section is divided in order to approximate the position data of the point sequence formed of the contour. In this case, the number of approximation sections may be a number sufficient to maintain a predetermined approximation accuracy when approximation is performed by a cubic spline function. Next, in step ST54, the position data of one of the divided approximate sections is approximated using a cubic spline function.

Next, proceeding to step ST55, it is determined whether or not the approximate position data obtained in the previous step falls within a range of a predetermined approximate accuracy. That is,
It is determined whether the value of the function has converged.

If the approximate position data falls within the range of the predetermined approximate accuracy (YES), the process proceeds to step ST56, in which the approximate position data of the section is stored and stored in a memory (not shown). Next, in step ST57, it is determined whether or not the approximation has been completed for all the divided approximation sections. If NO, the process returns to step ST54, where YE
In the case of S, the approximation ends.

If the approximate position data is out of the range of the predetermined approximate accuracy and the answer is NO, the process proceeds to step ST58, where the section is approximated based on the cubic Bezier function, and the obtained approximate In step ST56, the position data is stored as approximate position data of the section in the same manner as described above.

Also in this embodiment, a reproduced figure having a high approximation accuracy similar to the reproduced figure shown in FIG. 5A was obtained.

It should be noted that the present invention is not limited to the above-described embodiments, but can be modified as needed.

[0037]

As described above, since the position data approximation method of the present invention is constructed and operates, a plurality of functions are appropriately used to accurately approximate position data with a small amount of approximate position data. In addition, the effects of shortening the approximate calculation time and reducing the amount of memory can be achieved.

[Brief description of the drawings]

FIG. 1 is a flowchart showing a case of approximation by a position data approximation method of the present invention.

FIG. 2 is a flowchart showing another example of approximation by the position data approximation method of the present invention.

FIG. 3 is an explanatory diagram showing a process of determining approximation accuracy.

FIG. 4 is an explanatory diagram showing a point sequence of a process of determining approximation accuracy;

FIG. 5 (a) is a reproduction diagram approximated by the method of the present invention,
(B) is a reproduction diagram approximated by a conventional method, and (c) is a diagram showing an original figure to be approximated.

FIG. 6 is a flowchart showing still another case of approximation by the position data approximation method of the present invention.

FIG. 7 is a flowchart showing a case of approximation by a conventional approximation method;

Claims (1)

(57) [Claims] 1. A method of approximating position data in the form of a sequence of points using a plurality of functions to obtain approximate position data, wherein the approximate position data by an arbitrary function falls within a predetermined accuracy range. In this case, an approximation is performed using the function, and when the approximate position data is out of the predetermined accuracy range, the approximation is performed using another function.