CN106757816B - Method for adding shape information - Google Patents
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- CN106757816B CN106757816B CN201510818398.4A CN201510818398A CN106757816B CN 106757816 B CN106757816 B CN 106757816B CN 201510818398 A CN201510818398 A CN 201510818398A CN 106757816 B CN106757816 B CN 106757816B
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- D—TEXTILES; PAPER
- D05—SEWING; EMBROIDERING; TUFTING
- D05B—SEWING
- D05B19/00—Programme-controlled sewing machines
- D05B19/02—Sewing machines having electronic memory or microprocessor control unit
- D05B19/04—Sewing machines having electronic memory or microprocessor control unit characterised by memory aspects
- D05B19/08—Arrangements for inputting stitch or pattern data to memory ; Editing stitch or pattern data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/12—Cloth
Abstract
The invention provides a method for adding shape information, which comprises the following steps: acquiring sewing information in a non-NSP format pattern file; the sewing information comprises point sewing data, empty sending symbols and function codes; dividing the point seam data into a plurality of point seam data groups according to the positions of the idle sending character and the function code; performing shape fitting on the spot seam data in the spot seam data group by adopting a shape fitting algorithm to identify a corresponding pattern; and generating shape information for processing by an electronic pattern machine according to the recognized pattern. The method for adding the shape information can add the shape information according to the sewing information in the pattern file with the non-NSP format, and realizes the full-function editing of the pattern file by the electronic pattern sewing machine.
Description
Technical Field
The invention relates to the technical field of sewing of pattern sewing machines, in particular to a method for adding shape information.
Background
The electronic pattern sewing machine is a precision electromechanical integrated intelligent sewing device widely used in the industries of clothing, shoemaking, bags and the like, enables the traditional manual pattern to be realized at high speed and high efficiency, and is an electromechanical product which embodies various high and new technologies. And matched embroidery software or drawing software can carry out digital pattern design to generate a pattern file so as to meet the requirements of complexity and diversity of patterns.
The pattern file has various formats, for example: the format of the pattern file generated by the DOS version Tianmu software is named ndp, and the format of the pattern file generated by the Windows version Tiandao software is named emb. Moreover, with the development of computer technology, more and more complex or large patterns are generated by drawing software, such as: the pattern file generated by automatic Computer Aided Design (AutoCAD) software has the format of dxf. Among the pattern files in the format, the NSP format is a pattern format extended and derived by the hauser corporation on the basis of the mitsubishi B format, and the NSP format can recognize the following shapes: the NSP format brings great convenience for pattern editing by virtue of powerful composite element functions (including multiple seams, off-edge seams, backstitches, overlapped seams, herringbone seams and the like).
However, the non-NSP format pattern file only contains the position information of the needle track points, and the non-NSP format pattern file does not contain the shape information, so that the pattern editing function of the electronic pattern machine is limited due to the lack of the shape information.
Disclosure of Invention
The invention provides a method for adding shape information, which can add shape information according to sewing information in a pattern file with a non NSP format and realize full-function editing of the pattern file by an electronic pattern sewing machine.
The method for adding the shape information comprises the following steps:
acquiring sewing information in a non-NSP format pattern file; the sewing information comprises point sewing data, empty sending symbols and function codes;
dividing the point seam data into a plurality of point seam data groups according to the positions of the idle sending character and the function code;
performing shape fitting on the spot seam data in the spot seam data group by adopting a shape fitting algorithm to identify a corresponding pattern;
and generating shape information for processing by an electronic pattern machine according to the recognized pattern.
The invention provides a method for adding shape information, which comprises the following steps: the method comprises the steps of obtaining sewing information in a non-NSP format pattern file, dividing spot sewing data into a plurality of spot sewing data groups according to the positions of an idle delivery character and a function code, carrying out shape fitting on the spot sewing data in the spot sewing data groups by adopting a shape fitting algorithm, identifying corresponding pattern patterns, and generating shape information for an electronic pattern machine to process according to the identified pattern patterns. According to the method for adding the shape information, the spot sewing data are divided into a plurality of groups of spot sewing data groups according to the idle delivery character and the function code, the shape fitting is carried out on each spot sewing data group by adopting the shape fitting algorithm, the corresponding pattern is identified, so that the shape information processed by the electronic pattern sewing machine is generated according to the sewing information in the non-NSP format pattern file, and the full-function editing of the pattern file by the electronic pattern sewing machine is realized due to the shape information.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flowchart of a method for adding shape information according to an embodiment of the present invention;
fig. 2A to 2D are flowcharts of a method for adding shape information according to a second embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a flowchart of a method for adding shape information according to an embodiment of the present invention. As shown in fig. 1, the method for adding shape information provided by this embodiment may include:
The sewing information comprises point sewing data, empty sending symbols and function codes.
The non-NSP format pattern file usually contains (or contains after conversion) the position information of the trace points, and the position information of the trace points can be converted into the stitch data, the idle sending characters and the function codes in the NSP format pattern file. The stitch data refers to an increment of a trace point in the x-axis direction and the y-axis direction, and the function code refers to instruction information or mark information, for example: the clip command, the pause command, and the like are empty pointers.
And 103, dividing the spot seam data into a plurality of spot seam data groups according to the positions of the idle sending symbols and the function codes.
Wherein each spot seam data set comprises at least two spot seam data.
In this step, all the pieces of the stitch data in the pattern file are separated by using the dummy transport character and the function code as the space symbols, and thus the pieces of the stitch data between the dummy transport character and the dummy transport character, the pieces of the stitch data between the spacer character and the spacer character, and the pieces of the stitch data between the dummy transport character and the spacer character are separated. For each segment of separated seam data, only one piece of seam data may be included, that is, discrete seam data, or a plurality of pieces of continuously distributed seam data may be included, and the plurality of pieces of continuously distributed seam data are used as a seam data group.
And 105, performing shape fitting on the spot seam data in the spot seam data group by adopting a shape fitting algorithm, and identifying a corresponding pattern.
For the empty sending character, the function code and the discrete point seam data, only the reservation is needed, and for each point seam data group, the shape fitting algorithm is adopted to carry out shape fitting on the point seam data in the point seam data group so as to identify the pattern corresponding to the point seam data group.
Wherein, the pattern can be: straight lines, circles, arcs, curves, and the like.
The shape fitting algorithm may be an existing shape fitting algorithm, which is not limited in this embodiment. For example: the shape fitting algorithm may be at least one of a straight line fitting algorithm, a circular arc fitting algorithm, and a curve fitting algorithm.
And step 107, generating shape information for processing by the electronic pattern machine according to the recognized pattern.
In the step, the shape information which can be processed by the electronic pattern machine is generated according to the recognized pattern patterns, and the electronic pattern machine can edit full-function patterns with the shape information, so that the problem that the full-function editing is limited due to the lack of the shape information in the prior art is solved.
Optionally, after step 107, the method may further include:
and deleting the sewing data in the shape information, and generating sewing data with uniform stitches according to the shape information after the sewing data is deleted.
The length between two stitches is called the needle pitch, and the needle pitch can be set as required.
Because the stitch data in the non-NSP format pattern file may not be uniformly distributed, that is, the stitch length among the stitch data is not uniform, the problem of 'big and small stitches' exists, because the shape information which can be processed by the electronic pattern machine is generated through the step 101 to the step 107, the stitch data is deleted from the shape information, that is, the stitch data on the pattern is deleted, the sewing data with uniform stitches is regenerated only according to the shape information, and the problem of 'big and small stitches' is solved on the premise of ensuring that the pattern is not changed.
The embodiment provides a method for adding shape information, which comprises the following steps: the method comprises the steps of obtaining sewing information in a non-NSP format pattern file, wherein the sewing information comprises spot sewing data, empty sending symbols and function codes, dividing the spot sewing data into a plurality of spot sewing data groups according to the positions of the empty sending symbols and the function codes, carrying out shape fitting on the spot sewing data in the spot sewing data groups by adopting a shape fitting algorithm, identifying corresponding pattern patterns, and generating shape information for an electronic pattern machine to process according to the identified pattern patterns. According to the method for adding the shape information, the spot sewing data are divided into a plurality of groups of spot sewing data groups according to the idle delivery character and the function code, the shape fitting is carried out on each spot sewing data group by adopting the shape fitting algorithm, the corresponding pattern is identified, so that the shape information processed by the electronic pattern sewing machine is generated according to the sewing information in the non-NSP format pattern file, and the full-function editing of the pattern file by the electronic pattern sewing machine is realized due to the shape information.
Fig. 2A to 2D are flowcharts of a method for adding shape information according to a second embodiment of the present invention, and this embodiment provides a specific implementation manner of step 105 on the basis of the first embodiment. As shown in fig. 2, in this embodiment, the performing shape fitting on the stitch data in the stitch data set by using a shape fitting algorithm to identify a corresponding pattern may include:
step 1, judging whether preset numerical value unfit spot seam data exist in a spot seam data group.
If yes, turning to step 2; if not, the process goes to step 5.
In this step, it is necessary to determine whether there are enough unfit spot seam data in the spot seam data group for performing shape fitting, if the spot seam data are enough, shape fitting is necessary, and if the spot seam data are too little, shape fitting is not necessary.
Wherein, the preset value can be set as required, for example: set to 3.
And 2, adopting a straight line fitting algorithm to perform shape fitting on the preset numerical value point seam data and judging whether the preset numerical value point seam data are successfully fitted into a straight line.
If not, turning to the step 3; if yes, go to step 6.
In the step, the preset numerical value point seam data is subjected to shape fitting, firstly, the shape is tried out from the straight line shape, and if the straight line shape is not satisfied, the next shape is tried out.
And 3, adopting an arc fitting algorithm to perform shape fitting on the preset numerical value point seam data, and judging whether the preset numerical value point seam data are successfully fitted into an arc.
If not, turning to the step 4; if yes, go to step 9.
In the step, the preset numerical value point seam data is subjected to shape fitting, the arc shape is tried, and if the arc shape is not satisfied, the next shape is tried.
And 4, adopting a curve fitting algorithm to perform shape fitting on the preset numerical value point seam data, and judging whether the preset numerical value point seam data are successfully fitted into a curve.
If not, turning to the step 5; if yes, go to step 12.
In the step, the preset numerical value point seam data is subjected to shape fitting, the curve shape is probed, and if the curve shape is not satisfied, the probing of the next shape is not performed.
And 5, reserving the unmatched point seam data in the point seam data group as discrete point seam data.
If the unfit slit data in the slit data group is too little, shape fitting is not needed, or if the preset numerical value slit data cannot be successfully fitted to the shape through probing of a straight line shape, a circular arc shape and a curve shape, the unfit slit data in the slit data group is reserved as discrete slit data.
And 6, judging whether the unfit spot seam data exist in the spot seam data group.
If yes, turning to step 7; if not, go to step 8.
Because the preset numerical value point seam data are successfully fit into a straight line shape, whether unfit point seam data exist in the point seam data group or not needs to be judged, and if the unfit point seam data exist, the straight line shape fitting needs to be continuously carried out on the next unfit point seam data.
The straight line fitting algorithm in this step may be any one of the existing straight line fitting algorithms, and this embodiment does not limit this.
Optionally, for the straight line fitting algorithm, one implementation may be: determining a straight line by two pieces of point seam data, recording the direction of the straight line, calculating the distance from the next piece of point seam data to the straight line, finishing fitting if the distance from the point seam data to the straight line is greater than a preset threshold value, judging that the point seam data cannot be fitted on the straight line, successfully fitting if the distance from the point seam data to the straight line is less than the preset threshold value and the vector direction is the same as the direction of the straight line, judging that the point seam data can be fitted on the straight line, and continuing to fit the next piece of point seam data until the fitting cannot be successful.
The preset threshold value can be set according to needs.
And 8, recognizing the corresponding spot sewing data as a linear pattern.
In this step, the stitch data that can be successfully fitted into a straight shape is recognized as a straight pattern.
And 9, judging whether the unfit spot seam data exist in the spot seam data group.
If yes, turning to step 10; if not, go to step 11.
Because the preset numerical value seam data are successfully fitted into the arc shape, whether unfit seam data exist in the seam data group or not needs to be judged, and if the unfit seam data exist, the arc shape fitting needs to be continuously carried out on the next unfit seam data.
Step 10, adopting an arc fitting algorithm to perform shape fitting on next spot seam data in the spot seam data set, judging whether the next spot seam data is successfully fitted into an arc, if so, continuing adopting the arc fitting algorithm to perform shape fitting on the next spot seam data in the spot seam data set until the next spot seam data cannot be successfully fitted into the arc, and executing step 11; if not, the step 1 is started again.
The arc fitting algorithm in this step may be any existing arc fitting algorithm, which is not limited in this embodiment.
Optionally, for the arc fitting algorithm, one implementation may be: determining an arc with an obtuse included angle through three seam data which are not on the same straight line, recording the direction of the arc, calculating the distance from the next seam data to the arc, finishing fitting if the distance from the seam data to the arc is greater than a preset threshold value, judging that the seam data cannot be fitted on the arc, successfully fitting if the distance from the seam data to the arc is less than the preset threshold value and the vector direction is the same as the direction of the arc, judging that the seam data can be fitted on the arc, and continuing to fit the next seam data until the seam data cannot be fitted successfully.
The preset threshold value can be set according to needs.
And 11, recognizing the corresponding spot sewing data as an arc pattern, judging whether the starting point and the end point of the arc pattern coincide with each other or not, and recognizing the arc pattern as a circular pattern if the starting point and the end point of the arc pattern coincide with each other.
In this step, the stitch data that can be successfully fitted into the circular arc shape is identified as a circular arc pattern. If the starting point and the end point of the circular arc pattern coincide with each other, the circular arc is determined to be a circle, and the circular arc pattern is recognized as the circular seam data that can be successfully fitted into the circular arc shape.
And step 12, judging whether the unfit point seam data exist in the point seam data group.
If yes, go to step 13; if not, go to step 14.
Because the preset numerical value seam data are successfully fitted into the curve shape, whether unfit seam data exist in the seam data group or not needs to be judged, and if the unfit seam data exist, curve shape fitting needs to be continuously carried out on the next unfit seam data.
Step 13, adopting a curve fitting algorithm to perform shape fitting on next point seam data in the point seam data set, judging whether the next point seam data is successfully fitted into a curve, if so, continuing adopting the curve fitting algorithm to perform shape fitting on the next point seam data in the point seam data set until the next point seam data cannot be successfully fitted into the curve, and executing step 14; if not, the step 1 is started again.
The curve fitting algorithm in this step may be any existing curve fitting algorithm, which is not limited in this embodiment.
Optionally, for the curve fitting algorithm, one implementation may be: determining a curve with a three-point included angle larger than a preset angle through three seam data which are not on the same straight line, recording the direction of the curve, calculating the included angle formed by the next seam data and the last two seam data on the curve, if the included angle is smaller than the preset angle, finishing fitting, judging that the seam data cannot be fitted on the curve, if the included angle is larger than the preset angle, successfully fitting, judging that the seam data can be fitted on the curve, and continuing to fit the next seam data until the seam data cannot be fitted.
Wherein, the preset angle can be set according to the requirement.
And 14, identifying the corresponding spot sewing data as a curve pattern.
In this step, the stitch data that can be successfully fit into the curved shape is identified as a curved pattern.
In summary, through the steps 1 to 14, the seam data in the seam data set are tentatively fitted point by point, and if one shape is not successful, another shape is tentatively fitted, so that the pattern corresponding to the whole seam data set can be identified.
In addition, in the present embodiment, shape fitting is performed on the seam data in the seam data set, and according to the accuracy and complexity of the shape fitting, a straight line, an arc, and a curve are adopted in the heuristic order of the shape. As for shape fitting, discrete point seam data do not need to be fitted, the difficulty priority is the lowest, when fitting of other shapes fails, the discrete point seam data are naturally reserved, for the plurality of point seam data, the curve shape can be fitted as long as formed corners are not too sharp, the fitting difficulty of the arc is higher than that of the curve, and the fitting difficulty of the straight line is higher than that of the arc, so that the idea of difficulty-first-later-easy shape fitting is carried out by adopting the idea of difficulty-first trial, and the accuracy of shape fitting can be improved.
It should be noted that, in this embodiment, the heuristic order of the shapes may also adopt other heuristic orders, and this embodiment is not limited to this.
Optionally, the method may further include:
after the shape fitting is carried out on the current spot sewing data subjected to the shape fitting in the spot sewing data group by adopting any one of a straight line fitting algorithm and an arc fitting algorithm, if the shape fitting is successful, the pattern which is successfully fitted at present is corrected by adopting a least square algorithm to obtain the currently corrected pattern, and the shape fitting is continuously carried out on the next spot sewing data in the spot sewing data group on the basis of the currently corrected pattern until the pattern corresponding to the spot sewing data group is identified.
Specifically, step 7 is:
adopting a straight line fitting algorithm to perform shape fitting on the next point seam data in the point seam data set, judging whether the next point seam data is successfully fitted into a straight line, if so, correcting the straight line by adopting a least square algorithm, continuing adopting the straight line fitting algorithm to perform shape fitting on the next point seam data in the point seam data set until the next point seam data cannot be successfully fitted into the straight line, and executing the step 8; if not, the step 1 is started again.
Specifically, the step 10 is:
adopting an arc fitting algorithm to perform shape fitting on next spot seam data in the spot seam data set, judging whether the next spot seam data are successfully fitted into an arc, if so, correcting the arc by adopting a least square algorithm, continuing adopting the arc fitting algorithm to perform shape fitting on the next spot seam data in the spot seam data set until the next spot seam data cannot be successfully fitted into the arc, and executing the step 11; if not, the step 1 is started again.
Therefore, for the straight line fitting algorithm and the circular arc fitting algorithm, the accuracy of the fitted straight line shape, circular arc shape or circular shape is further ensured by adopting a point-by-point fitting and point-by-point correction mode.
When the shape fitting algorithm is adopted to perform shape fitting on the spot seam data in the spot seam data group, according to the accuracy and complexity of the shape fitting, the fitting sequence of straight lines, circular arcs and curves is adopted, and shape tentative fitting is performed according to the sequence of the shape fitting from difficult to easy, so that the accuracy of the shape fitting is improved, the pattern and the pattern corresponding to the recognized spot seam data group are more accurate, and further pattern editing is facilitated.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (3)
1. A method of adding shape information, comprising:
acquiring sewing information in a non-NSP format pattern file; the sewing information comprises point sewing data, empty sending symbols and function codes;
dividing the point seam data into a plurality of point seam data groups according to the positions of the idle sending character and the function code;
performing shape fitting on the spot seam data in the spot seam data group by adopting a shape fitting algorithm, and identifying a corresponding pattern, wherein the shape fitting algorithm is at least one of a straight line fitting algorithm, an arc fitting algorithm and a curve fitting algorithm;
when the shape fitting is carried out on the point seam data in the point seam data group, the use priority of the straight line fitting algorithm is higher than that of the circular arc fitting algorithm, and the use priority of the circular arc fitting algorithm is higher than that of the curve fitting algorithm;
generating shape information for processing by an electronic pattern machine according to the recognized pattern;
the shape fitting of the spot seam data in the spot seam data group by using the shape fitting algorithm to identify the corresponding pattern specifically comprises the following steps:
step 1, judging whether a preset number of unfit spot seam data exist in the spot seam data group; if yes, turning to step 2; if not, turning to the step 5;
step 2, adopting the straight line fitting algorithm to perform shape fitting on the preset numerical value point seam data and judging whether the preset numerical value point seam data are successfully fitted into a straight line; if not, turning to the step 3; if yes, turning to step 6;
step 3, adopting the arc fitting algorithm to perform shape fitting on the preset numerical value point seam data and judging whether the preset numerical value point seam data are successfully fitted into an arc; if not, turning to the step 4; if yes, turning to step 9;
step 4, adopting the curve fitting algorithm to perform shape fitting on the preset numerical value point seam data and judging whether the preset numerical value point seam data are successfully fitted into a curve or not; if not, turning to the step 5; if yes, go to step 12;
step 5, retaining the unfit point seam data in the point seam data group as discrete point seam data;
step 6, judging whether unmatched point seam data exist in the point seam data group or not; if yes, turning to step 7; if not, turning to step 8;
step 7, adopting the straight line fitting algorithm to perform shape fitting on the next point seam data in the point seam data group, and judging whether the next point seam data is successfully fitted into a straight line; if so, continuing to adopt the straight line fitting algorithm to perform shape fitting on the next point seam data in the point seam data group until the next point seam data cannot be successfully fitted into a straight line; if not, the step 1 is started again;
step 8, recognizing the corresponding spot sewing data as a linear pattern;
step 9, judging whether the unfit spot seam data exist in the spot seam data group; if yes, turning to step 10; if not, turning to step 11;
step 10, adopting the arc fitting algorithm to perform shape fitting on the next point seam data in the point seam data group, and judging whether the next point seam data is successfully fitted into an arc; if so, continuing to adopt the arc fitting algorithm to perform shape fitting on the next point seam data in the point seam data group until the next point seam data cannot be successfully fitted into an arc; if not, the step 1 is started again;
step 11, identifying the corresponding spot sewing data as an arc pattern; judging whether the starting point and the end point of the circular arc pattern coincide with each other or not; if so, identifying the circular arc pattern as a circular pattern;
step 12, judging whether the unfit spot seam data exist in the spot seam data group; if yes, go to step 13; if not, turning to step 14;
step 13, adopting the curve fitting algorithm to perform shape fitting on the next point seam data in the point seam data group, and judging whether the next point seam data is successfully fitted into a curve; if so, continuing to adopt the curve fitting algorithm to perform shape fitting on the next point seam data in the point seam data group until the next point seam data cannot be successfully fitted into a curve; if not, the step 1 is started again;
step 14 identifies the corresponding stitch data as a curvilinear pattern.
2. The method of claim 1, further comprising:
after the shape fitting is carried out on the current spot sewing data subjected to the shape fitting in the spot sewing data group by adopting any one of a straight line fitting algorithm and an arc fitting algorithm, if the shape fitting is successful, the pattern which is successfully fitted at present is corrected by adopting a least square algorithm to obtain the currently corrected pattern, and the shape fitting is continuously carried out on the next spot sewing data in the spot sewing data group on the basis of the currently corrected pattern until the pattern corresponding to the spot sewing data group is identified.
3. The method according to any one of claims 1-2, wherein after generating the shape information for processing by an electronic pattern machine based on the identified pattern of patterns, further comprising:
deleting the stitch data in the shape information;
and generating sewing data with uniform stitches according to the shape information of the deleted sewing data.
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| DE59605161D1 (en) * | 1995-07-14 | 2000-06-15 | Gegauf Fritz Ag | Method for designing the program memory of an electronic sewing machine, sewing machine for carrying out this method and use of the sewing machine |
| JP3864877B2 (en) * | 2002-09-11 | 2007-01-10 | ブラザー工業株式会社 | Staggered sewing machine |
| CN101751515B (en) * | 2009-12-10 | 2012-01-18 | 西北工业大学 | Method for customizing tailoring pattern and generating tailoring data |
| CN102634933A (en) * | 2012-04-19 | 2012-08-15 | 南京理工大学常熟研究院有限公司 | Pattern editing and pattern generating method for electronic pattern machine |
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