CN112507404B - Variable cutting track generation method of borderless image - Google Patents
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Abstract
The invention relates to a variable cutting track generation method of borderless images, and belongs to the field of automatic cutting. The invention obtains a basic image through an image obtaining device; establishing a corresponding relation between the basic image and the cutting track and storing the corresponding relation as priori knowledge in a knowledge base; selecting priori knowledge from a knowledge base; in the printing material cutting production process, the selected characteristic template is utilized to match the acquired image to obtain the position of the basic image, and then the cutting track is automatically generated at the corresponding position of the cutting bed through the processing of coordinate transformation of the cutting bed, data grouping after transformation, mapping and matching of the cutting track position relation track and the like. The automatic alignment method can meet the requirement of the same cutting material on automatic generation of the cutting track of the automatic alignment of the periodical printing material with different cutting requirements, and solves the problems that the cutting track of the printing material without obvious cutting track is difficult to extract and the flexible and changeable cutting requirements are difficult to meet.
Description
Technical Field
The invention relates to a method, in particular to a variable cutting track generation method of borderless images, which is a method for automatically generating a cutting track of a periodical printing material without obvious border tracks, and belongs to the field of automatic cutting.
Background
The printing material in the cutting industry has rich patterns, various shapes and varied cutting requirements. The automatic generation of the cutting track is realized by utilizing the machine vision technology, so that a customer can conveniently use intelligent cutting equipment to realize automatic production, and the production efficiency of products is remarkably improved.
The current method needs to outline the cutting track of the printing material by using outstanding colors, and the color difference between the cutting track and the background is obvious, and secondly, the typesetting interval between the cutting sample pieces is increased, such as 5 mm typesetting interval amount, during printing typesetting. The method can increase material waste and can not solve the problem that different cutting tracks are required to be realized when the same printing material is produced. In addition, some printed materials cannot be added with additional cutting tracks due to the manufacturing process, and in the case of the situation, the printed materials can be cut manually.
The publication date is 2015, 05 and 06, and the Chinese patent with publication number CN104599267A discloses an invention patent named as a cutting track generation method and device. The cutting track generation method of the patent comprises the following steps: acquiring an object to be cut; extracting the outline of an object to be cut; receiving array parameters, wherein the array parameters are used for indicating batch generation of cutting tracks of objects to be cut, and the array parameters comprise row numbers, column numbers, row-column pitches and cutting sequences; and generating a cutting track of the object to be cut according to the outline of the object to be cut and the array parameters. Although this patent solves the problem of low cutting efficiency of objects such as images or vector graphics, it does not solve the problem of the need to cut the same-width printed material to achieve different cutting tracks, so it still has the above-mentioned drawbacks.
Therefore, it is particularly necessary to provide an automatic identification and positioning research for periodic printing materials without obvious boundary cutting tracks in the cutting industry.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides the automatic generation method of the cutting track of the automatic alignment of the periodical printing material, which can meet the same cutting material to realize different cutting requirements, and meet the cutting requirements of intelligent production cutting based on flexible variation of borderless images of the image technology.
The invention solves the problems by adopting the following technical scheme: the variable cutting track generation method of the borderless image is characterized by comprising the following steps of: the method comprises the following steps:
(S1) establishing prior knowledge of the cut
1) Obtaining a basic image;
2) And (3) manufacturing a basic image template: k basic image blocks with unique characteristics are manufactured as a basic image template set Match: { matchContourr 1, matchContourr 2, …, matchContourk }, k is greater than or equal to 1, each matchContouri representing a base image block with unique essential features;
3) Establishing a basic characteristic vector track set BasicContours corresponding to a basic image template set Match, and recording as follows: { BasicContourr 1, basicContourr 2, …, basicContourk }, k.gtoreq.1;
4) Establishing a corresponding relation epsilon under a unified image coordinate system, namely establishing a one-to-one corresponding position relation between a basic image template set Match { matchContourr 1, matchContourr 2, …, matchContourk }, k is more than or equal to 1, and a basic feature vector track set BasicContourr { BasicContourr 1, basicContourr 2, …, basicContourk }, and k is more than or equal to 1;
5) Converting the basic characteristic vector locus set BasicContourr into a cutting bed coordinate BasicContourCut set, basicContourCut= { BasicContourCut1, basicContourCut2, …, basicContourCutk }, and k is more than or equal to 1;
6) A vector cutting track set OutPutContourt under a cutting coordinate system to be cut is produced or imported and recorded as follows: { OutPutContourr 1, outPutContourr 2, …, outPutContourn }, n.;
7) Under a cutting coordinate system, defining a grouping rule ∈according to the cutting requirement of a customer, grouping a cutting bed coordinate BasicContourcut set of a basic feature vector track set by the rule, and defining a cutting track mapping set sigma corresponding to each grouping; wherein,
(1) the grouping rules ∈ are expressed as follows:
dividing the corresponding cut-bed coordinate BasicContourCut set of the basic feature vector track set into n groups of BasicContourCutGroup= { BasicContourCutGroup1, …, basicContourCutGroupn }, each group comprising a plurality of basic feature vectors, the number of basic feature vectors of each group being unequal, and the groups being disjoint;
the BasicContourCutGroup group members are represented as follows:
BasicContourCutGroup1＝{BasicContourCut1，BasicContourCut2，…，BasicContourCut-o 1 }，
BasicContourCutGroup2＝{BasicContourCut-o 1 +1，BasicContourCut-o 1 +2，…，BasicContourCut-o 2 }，
…，
BasicContourCutGroupn＝{BasicContourCut-Cut-o n-1 +1，BasicContourCut-o n-1 +2, …, basic ContourCutk, divided into n total groups;
(2) establishing the basic feature vector track grouping
A mapping set sigma of the corresponding positional relationship of basiccount group= { basiccount group1, …, basiccount group } and vector cut trajectory set outputContour= { outputContour1, outputContour2, …, outputContourn };
(S2) establishing a knowledge base of the corresponding relation between the printed pattern material and the matched cutting track;
(S3) selecting the matching relation according to the cutting requirement;
(S4) the camera acquires an image Picture of the material to be cut;
(S5) automatically generating a cutting track by using the acquired matching relation of the knowledge base, wherein the cutting track is specifically as follows:
1) The method comprises the steps that elements in a basic image template set { matchContourl 1, matchContourl 2, …, matchContourk }, k is larger than or equal to 1, the acquired images Picture are matched one by one to obtain the positions of basic image template combined elements in the Picture, { matchContourl 1, matchContourl 2, …, matchContourk }1, { matchContourl 1, matchContourl 2, …, matchContourk }2, … { matchContourl 1, matchContourl 2, …, matchContourk } q, q is larger than or equal to 1, and the image acquisition comprises the positions of q complete basic image template sets in the Picture;
2) Obtaining basic vector track data { basic Contourr 1, basic Contourr 2, …, basic Contourk }1, { basic Contourr 1, basic Contourr 2, …, basic Contourk }2, … { basic Contourr 1, basic Contourr 2, …, basic Contourk } q corresponding to the basic template set of the q matched positions by using the corresponding relation epsilon of the basic image template set and the basic feature vector track set;
3) Converting { BasicContourr 1, basicContourr 2, …, basicContourk }1, { BasicContourr1, basicContourr 2, …, basicContourk }2, … { BasicContourr 1, basicContourr 2, …, basicContourk } q into a corresponding set of BasicContourCut in the cutting bed coordinate system;
4) And (3) according to a selected grouping rule (Ench), respectively and independently grouping q groups of the result BasicContourCut in sequence, wherein the grouping result is expressed as follows:
Group1＝{BasicContourCutGroup1{}，…，…，BasicContourGroupn{}}1
，…，
Groupq＝{BasicContourCutGroup1{}，…，…，BasicContourGroupn{}}q；
5) Based on the result, the grouped result is sequentially converted into a cutting track set CutContourr= { on the cutting bed according to the corresponding relation sigma
{OutPutContour1，OutPutContour2，…，OutPutContourn}1，
，…，
{OutPutContour1，OutPutContour2，…，OutPutContourn}q}；
6) CutContour is taken as the cutting track of the current scanning image, the cutting track generated by the current identification matching is output to the equipment, and the equipment controls the cutting equipment to complete the task according to the track.
Preferably, in the step (S1) of the present invention, a basic feature vector locus basic content set corresponding to the basic image template set Match is established, and elements of the basic content may be rectangular or directly vector data under an image coordinate system corresponding to the cutting locus data.
Preferably, 7) in the step (S1) of the present invention defines a grouping rule ∈ContourCut of the basic feature vector trajectory set according to the cutting requirement of the client under the same coordinate system, and defines a cutting trajectory mapping set sigma corresponding to each grouping. Wherein,
(1) the grouping rules ∈ are expressed as follows:
the basic feature vector track set is divided into n groups of basic feature vector sets = { basic feature vector sets 1, …, basic feature vector sets }, each group comprises a plurality of basic feature vectors, the number of the basic feature vectors of each group can be unequal, and the groups are disjoint.
(2) Establishing the basic feature vector track grouping
A mapping set sigma of the corresponding positional relationship of basiccount group= { basiccount group1, …, basiccount group } and vector cut trajectory set outputContour= { outputContour1, outputContour2, …, outputContourn };
preferably, in the step (S2), the knowledge base record includes a print pattern image index, a base image template set Match, a correspondence epsilon between a base feature vector track BasicContour, match and a base content, a plurality of vector cut track sets outputcontent, a cutting bed coordinate base content set grouping rule of the base feature vector track set, a mapping set sigma of a corresponding position relation between a base feature vector track grouping base content set group and a vector cut track set outputcontent. The OutPutContourr, grouping rule +.and mapping set sigma corresponding to each printing pattern may not be unique and may be defined according to the actual cutting requirement.
Compared with the prior art, the invention has the following advantages and effects: the automatic generation of the cutting track of the automatic alignment of the periodical printing materials with different cutting requirements can be realized by the same type of cutting materials, the difficult problems that the cutting track of the printing materials without obvious cutting tracks is difficult to extract and the flexible changing cutting requirements are difficult to meet are solved, and a technical foundation is provided for the intelligent production and cutting of the printing materials.
Drawings
FIG. 1 is a schematic flow chart of a production method according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of correspondence between a base image and a cutting track according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail by way of examples with reference to the accompanying drawings, which are illustrative of the present invention and not limited to the following examples.
Examples.
Referring to fig. 1 to 2, the method for generating a variable cutting track without boundary image according to the present embodiment includes the following steps:
(S1) establishing prior knowledge of the cut
1) A base image is obtained.
2) Making basic image templates, namely making k basic image blocks with unique characteristics as basic image template sets Match: { matchContourr 1, matchContourr 2, …, matchContourk }, k. Gtoreq.1, each matchContouri represents a basic image block with unique necessary characteristics.
3) The elements of the basic feature vector track set BasicContour, basicContour corresponding to the basic image template set Match can be rectangular or directly vector data under an image coordinate system corresponding to the cutting track data, and the elements are recorded as follows: { BasicContourr 1, basicContourr 2, …, basicContourk }, k.gtoreq.1;
4) Establishing a corresponding relation epsilon under a unified image coordinate system, namely establishing a one-to-one corresponding position relation between a basic image template set Match { matchContourr 1, matchContourr 2, …, matchContourk }, k is more than or equal to 1, and a basic feature vector track set BasicContourr { BasicContourr 1, basicContourr 2, …, basicContourk }, and k is more than or equal to 1;
5) Converting the basic characteristic vector locus set BasicContourr into a cutting bed coordinate BasicContourCut set, basicContourCut= { BasicContourCut1, basicContourCut2, …, basicContourCutk }, and k is more than or equal to 1;
6) A vector cutting track set OutPutContourt under a cutting coordinate system to be cut is produced or imported and recorded as follows: { OutPutContourr 1, outPutContourr 2, …, outPutContourn }, n.;
7) Under a cutting coordinate system, defining a grouping rule ∈according to the cutting requirement of a customer, grouping a cutting bed coordinate BasicContourcut set of a basic feature vector track set by the rule, and defining a cutting track mapping set sigma corresponding to each grouping; wherein,
(1) the grouping rules ∈ are expressed as follows:
the corresponding cut bed coordinates basic ContourCut set of the basic feature vector track set is divided into n groups of basic ContourCutGroup= { basic ContourCutGroup1, …, basic ContourCutGroupn }, each group comprises a plurality of basic feature vectors, the number of the basic feature vectors of each group can be unequal, and the groups are disjoint.
The BasicContourCutGroup group members are represented as follows:
BasicContourCutGroup1＝{BasicContourCut1，BasicContourCut2，…，BasicContourCut-o 1 }，
BasicContourCutGroup2＝{BasicContourCut-o 1 +1，BasicContourCut-o 1 +2，…，BasicContourCut-o 2 }，
…，
BasicContourCutGroupn＝{BasicContourCut-Cut-o n-1 +1，BasicContourCut-o n-1 +2, …, basic ContourCutk, divided into n total groups;
(2) establishing the basic feature vector track grouping
A mapping set sigma of the corresponding positional relationship of basiccount group= { basiccount group1, …, basiccount group } and vector cut trajectory set outputContour= { outputContour1, outputContour2, …, outputContourn };
(S2) establishing a knowledge base of the corresponding relation between the printed pattern material and the matched cutting track
The knowledge base record includes: the method comprises the steps of printing pattern image indexes, a basic image template set Match, a corresponding relation epsilon of basic feature vector tracks BasicContour, match and BasicContours, a plurality of vector cutting track sets OutPutContours, a cutting bed coordinate BasicContourCut set grouping rule of the basic feature vector track sets, and a mapping set sigma of the corresponding position relation between basic feature vector track groups BasicContourCutGroup and vector cutting track sets OutPutContours.
The knowledge base structure is as follows:
the OutPutContourr, grouping rule +.and mapping set sigma corresponding to each printing pattern may not be unique and may be defined according to the actual cutting requirement.
(S3) selecting the matching relation according to the cutting requirement;
(S4) the camera acquires an image Picture of the material to be cut;
and (S5) automatically generating a cutting track by using the acquired matching relation of the knowledge base, and calling a track generation program module, wherein the specific execution process of the module is as follows:
1) The method comprises the steps that elements in a basic image template set { matchContourl 1, matchContourl 2, …, matchContourk }, k is larger than or equal to 1, the acquired images Picture are matched one by one to obtain the positions of basic image template combined elements in the Picture, { matchContourl 1, matchContourl 2, …, matchContourk }1, { matchContourl 1, matchContourl 2, …, matchContourk }2, … { matchContourl 1, matchContourl 2, …, matchContourk } q, q is larger than or equal to 1, and the image acquisition comprises the positions of q complete basic image template sets in the Picture;
2) Obtaining basic vector track data { basic Contourr 1, basic Contourr 2, …, basic Contourk }1, { basic Contourr 1, basic Contourr 2, …, basic Contourk }2, … { basic Contourr 1, basic Contourr 2, …, basic Contourk } q corresponding to the basic template set of the q matched positions by using the corresponding relation epsilon of the basic image template set and the basic feature vector track set;
3) Converting { BasicContourr 1, basicContourr 2, …, basicContourk }1, { BasicContourr1, basicContourr 2, …, basicContourk }2, … { BasicContourr 1, basicContourr 2, …, basicContourk } q into a corresponding set of BasicContourCut in the cutting bed coordinate system;
4) And (3) according to a selected grouping rule (Ench), respectively and independently grouping q groups of the result BasicContourCut in sequence, wherein the grouping result is expressed as follows:
Group1＝{BasicContourCutGroup1{}，…，…，BasicContourGroupn{}}1
，…，
Groupq＝{BasicContourCutGroup1{}，…，…，BasicContourGroupn{}}q；
5) Based on the result, the grouped result is sequentially converted into a cutting track set CutContourr= { on the cutting bed according to the corresponding relation sigma
{OutPutContour1，OutPutContour2，…，OutPutContourn}1，
，…，
{OutPutContour1，OutPutContour2，…，OutPutContourn}q}；
6) CutContour is taken as the cutting track of the current scanning image, the cutting track generated by the current identification matching is output to the equipment, and the equipment controls the cutting equipment to complete the task according to the track.
The boundary of the basic image of the printed material of this embodiment is not a cutting trace, but has a correspondence relationship with the cutting trace as shown in fig. 2.
In practical application, firstly, calibrating a camera to obtain a conversion relation between an image and a cutting bed; selecting pattern indexes of printing materials in a cutting experience knowledge base to obtain priori knowledge, wherein the method comprises the following steps of: basic image template set Match, basic feature vector track basic Contours, corresponding relation epsilon between Match and basic Contours, certain grouping rule of basic Contourcut, vector cutting track set OutPutContouri, rule grouping of the rule and position relation mapping set sigma i.
And then, acquiring an image of the printed material to be cut through a camera, calling the program library to obtain corresponding cutting data, and matching the original cutting data to a position corresponding to a cutting bed, so that automatic cutting production of the printed material without obvious cutting tracks is realized.
The embodiment obtains a basic image through an image obtaining device; on the basis, establishing a corresponding relation between the basic image and the cutting track and storing the corresponding relation as priori knowledge in a knowledge base; selecting priori knowledge from a knowledge base; in the printing material cutting production process, a basic image template with unique characteristics is selected to match an acquired image to obtain the position of the basic image, then the corresponding position of a cutting track on a cutting bed is automatically generated through the processing of coordinate transformation of the cutting bed, data grouping after transformation, mapping matching of cutting track position relation tracks and the like, and the out PutContourr, data grouping rule and mapping set sigma corresponding to a certain printing pattern can be not unique and can be flexibly defined according to actual cutting needs.
From the above description, those skilled in the art will be able to practice.
In addition, it should be noted that the specific embodiments described in the present specification may vary from part to part, from name to name, etc., and the above description in the present specification is merely illustrative of the structure of the present invention. All equivalent or simple changes of the structure, characteristics and principle according to the inventive concept are included in the protection scope of the present patent. Those skilled in the art may make various modifications or additions to the described embodiments or substitutions in a similar manner without departing from the scope of the invention as defined in the accompanying claims.
Claims (4)
1. A variable cutting track generation method of borderless images is characterized in that: the method comprises the following steps:
(S1) establishing prior knowledge of the cut
1) Obtaining a basic image;
2) And (3) manufacturing a basic image template: k basic image blocks with unique characteristics are manufactured as a basic image template set Match: { matchContourr 1, matchContourr 2, …, matchContourk }, k is greater than or equal to 1, each matchContouri representing a base image block with unique essential features;
3) Establishing a basic characteristic vector track set BasicContours corresponding to a basic image template set Match, and recording as follows: { BasicContourr 1, basicContourr 2, …, basicContourk }, k.gtoreq.1;
4) Establishing a corresponding relation epsilon under a unified image coordinate system, namely establishing a one-to-one corresponding position relation between a basic image template set Match { matchContourr 1, matchContourr 2, …, matchContourk }, k is more than or equal to 1, and a basic feature vector track set BasicContourr { BasicContourr 1, basicContourr 2, …, basicContourk }, and k is more than or equal to 1;
5) Converting the basic characteristic vector locus set BasicContourr into a cutting bed coordinate BasicContourCut set, basicContourCut= { BasicContourCut1, basicContourCut2, …, basicContourCutk }, and k is more than or equal to 1;
6) A vector cutting track set OutPutContourt under a cutting coordinate system to be cut is produced or imported and recorded as follows: { OutPutContourr 1, outPutContourr 2, …, outPutContourn }, n.;
7) Under a cutting coordinate system, defining a grouping rule ∈according to the cutting requirement of a customer, grouping a cutting bed coordinate BasicContourcut set of a basic feature vector track set by the rule, and defining a cutting track mapping set sigma corresponding to each grouping; wherein,
(1) the grouping rules ∈ are expressed as follows:
dividing the corresponding cut bed coordinate BasicContourCut set of the basic feature vector track set into n groups of BasicContourCutGroup= { BasicContourCutGroup1, …, basicContourCutGroupn }, wherein each group comprises a plurality of basic feature vectors, the number of the basic feature vectors of each group is unequal, and the groups are not intersected; the BasicContourCutGroup group members are represented as follows:
BasicContourCutGroup1＝{BasicContourCut1，BasicContourCut2，…，BasicContourCut-o 1 }，
BasicContourCutGroup2＝{BasicContourCut-o 1 +1，
BasicContourCut-o 1 +2，…，BasicContourCut-o 2 }，
…，
BasicContourCutGroupn＝{BasicContourCut-Cut-o n-1 +1，BasicContourCut-o n-1 +2, …, basic ContourCutk, divided into n total groups;
(2) establishing the basic feature vector track grouping
A mapping set sigma of the corresponding positional relationship of basiccount group= { basiccount group1, …, basiccount group } and vector cut trajectory set outputContour= { outputContour1, outputContour2, …, outputContourn };
(S2) establishing a knowledge base of the corresponding relation between the printed pattern material and the matched cutting track;
(S3) selecting the matching relation according to the cutting requirement;
(S4) the camera acquires an image Picture of the material to be cut;
(S5) automatically generating a cutting track by using the acquired matching relation of the knowledge base, wherein the cutting track is specifically as follows:
1) The method comprises the steps that elements in a basic image template set { matchContourr 0, matchContourr 1, …, matchContourk }, k is larger than or equal to 1, the acquired images Picture are matched one by one to obtain the positions of basic image template combined elements in the Picture, { matchContourr 1, matchContourr 2, …, matchContourk }1, { matchContourr 1, matchContourr 2, …, matchContourk }2, … { matchContourr 1, matchContourr 2, …, matchContourk } q, q is larger than or equal to 1, and the image acquisition comprises the positions of q complete basic image template sets in the Picture;
2) Obtaining basic vector track data { basic Contourr 1, basic Contourr 2, …, basic Contourk }1, { basic Contourr 1, basic Contourr 2, …, basic Contourk }2, … { basic Contourr 1, basic Contourr 2, …, basic Contourk } q corresponding to the basic template set of the q matched positions by using the corresponding relation epsilon of the basic image template set and the basic feature vector track set;
3) Converting { BasicContourr 1, basicContourr 2, …, basicContourk }1, { BasicContourr1, basicContourr 2, …, basicContourk }2, … { BasicContourr 1, basicContourr 2, …, basicContourk } q into a corresponding set of BasicContourCut in the cutting bed coordinate system;
4) And (3) according to a selected grouping rule (E), respectively and independently grouping q groups of the results in sequence, wherein the grouping results are expressed as follows:
Group1＝{BasicContourCutGroup1{}，…，…，BasicContourGroupn{}}1，…，
Groupn＝{BasicContourCutGroup1{}，…，…，BasicContourGroupn{}}q；
5) Based on the result, the grouped result is sequentially converted into a cutting track set CutContourr= { on the cutting bed according to the corresponding relation sigma
{OutPutContour1，OutPutContour2，…，OutPutContourn}1，
…，
{OutPutContour1，OutPutContour2，…，OutPutContourn}q}；
6) CutContour is taken as the cutting track of the current scanning image, the cutting track generated by the current identification matching is output to the equipment, and the equipment controls the cutting equipment to complete the task according to the track.
2. The borderless image variable cutting trajectory generation method according to claim 1, characterized in that: and 3) establishing a basic characteristic vector locus basic content set corresponding to the basic image template set Match, wherein the elements of the basic content adopt rectangles or are vector data under an image coordinate system corresponding to the cutting locus data.
3. The borderless image variable cutting trajectory generation method according to claim 1, characterized in that: 7 in the step (S1), under the same coordinate system, defining a grouping rule ∈ContourCut of a basic feature vector track set according to the cutting requirement of a client, and defining a cutting track mapping set sigma corresponding to each grouping, wherein,
(1) the grouping rules ∈ are expressed as follows:
dividing the basic feature vector track set BasicContourCut into n groups of BasicContourCutGroup= { BasicContourCutGroup1, …, basicContourCutGroupn }, each group comprising a plurality of basic feature vectors, the number of basic feature vectors of each group being unequal, and the groups being disjoint;
(2) establishing the basic feature vector track grouping
The basic ContourCutGroup= { basic ContourCutGroup1, …, basic ContourCutGroupn } and the vector cut trajectory set OutPutContouru= { OutPutContourr 1, outPutContourr 2, …, outPutContourn }.
4. The borderless image variable cutting trajectory generation method according to claim 1, characterized in that: in the step (S2), the knowledge base record comprises a print pattern image index, a basic image template set Match, a corresponding relation epsilon between basic feature vector tracks BasicContour, match and basic Contours, a plurality of vector cutting track sets OutPutContours, a basic feature vector track set basic Contourcut grouping rule @, a mapping set sigma of the corresponding position relation between basic feature vector track groups basic ContourCutGroup and vector cutting track sets OutPutContours; the OutPutContourr, grouping rule ∈ and mapping set sigma corresponding to each printing pattern are not unique, and are defined according to actual cutting requirements.
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