CN102704215A - Automatic cutting method of embroidery cloth based on combination of DST file parsing and machine vision - Google Patents

Automatic cutting method of embroidery cloth based on combination of DST file parsing and machine vision Download PDF

Info

Publication number
CN102704215A
CN102704215A CN2012101218921A CN201210121892A CN102704215A CN 102704215 A CN102704215 A CN 102704215A CN 2012101218921 A CN2012101218921 A CN 2012101218921A CN 201210121892 A CN201210121892 A CN 201210121892A CN 102704215 A CN102704215 A CN 102704215A
Authority
CN
China
Prior art keywords
dst
image
sample
embroidery
file
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN2012101218921A
Other languages
Chinese (zh)
Other versions
CN102704215B (en
Inventor
李新德
金晓彬
曹久祥
张秀龙
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Southeast University
Original Assignee
Southeast University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Southeast University filed Critical Southeast University
Priority to CN 201210121892 priority Critical patent/CN102704215B/en
Publication of CN102704215A publication Critical patent/CN102704215A/en
Application granted granted Critical
Publication of CN102704215B publication Critical patent/CN102704215B/en
Expired - Fee Related legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Sewing Machines And Sewing (AREA)

Abstract

The invention discloses an automatic cutting method of embroidery cloth based on combination of DST file parsing and machine vision. In wool toy manufacturing industry, the profile and pattern of the wool toy are processed by adopting an embroidery machine, and the whole embroidery piece is cut one by one by adopting a laser cutter. The method comprises the steps of: firstly parsing a DST file (embroidery file) into an image file, selecting cutting units from the image file, and extracting the information of the cutting units to obtain the inside parameter of the unit; and carrying out correlated processing according to the image of cut sample obtained by camera shooting, matching the obtained cutting unit information with the processed sample, finally determining the cutting line position, generating a PLT file and cutting by a cutter. Different from other laser cutting methods based on machine vision, the method can finish cutting of the whole embroidery sample just by once shooting; and the method has the characteristics of high working efficiency and low unqualified rate, and has very strong cutting capability on the complicated embroidery sample.

Description

The automatic cutting method of embroidery cloth that combines with machine vision based on the DST document analysis
Technical field
The present invention relates to the automatic cutting method of a kind of embroidery cloth, based on combining of DST document analysis and machine vision.
Background technology
Present embroidery cloth laser cutting system mainly contains two kinds: a kind of is earlier on blank sheet of paper cutting once will embroider the cloth sample then and be placed on the cut surface, cut once again after the profile that cuts out on colored type and the blank sheet of paper embroidered on the cloth is alignd; Another kind is that camera is installed on laser cutting head, and colored type unit of every cutting will extract sample and handle once, promptly can only cut a colored type unit at every turn.Because so there is diced system to have inefficiency, therefore problems such as defect ware proportion height press for a kind of new cutting mode, in order to replace current mode.The develop rapidly of machine vision provides a kind of new thinking for we address the above problem.
Machine vision utilizes machine to replace human eye to do various measurements and judgement exactly.It is an important branch of computer subject, and it combines the technology of aspects such as optics, machinery, electronics, computer software and hardware, relates to a plurality of fields such as computer, image processing, pattern-recognition, artificial intelligence, signal processing, optical, mechanical and electronic integration.On production line, the people does this type of measurement and judgement meeting and produces the sum of errors mistake because of fatigue, person-to-person difference etc., but machine but can be tirelessly, stably go on.In general, NI Vision Builder for Automated Inspection has comprised illuminator, camera lens, camera system and image processing system.Use for each, the speed of service that we need taking into account system and image processing velocity, the size that detects target still detect target has that zero defect, visual field needs are much, height more than the resolution ratio needs, contrast needs are much etc.Typical NI Vision Builder for Automated Inspection can be divided into: IMAQ part, image processing section and motion control part.
The groundwork process of a complete NI Vision Builder for Automated Inspection is following:
1, camera is taken pictures according to instruction, and its time for exposure preestablishes;
2, IMAQ partly receives the DID after the video camera digitlization, and it is deposited in processor or the calculator memory;
3, measurement result or logic control value are handled, analyze, discern, obtained to processor to image;
4, the error of the action of result control streamline, location, correction campaign etc.
Summary of the invention
Goal of the invention: low in order to overcome the operating efficiency that exists in the prior art, stock utilization is low, and cost is than problems such as height.The present invention has solved the shortcoming that original diced system scientific and technological content and operating efficiency are low, defect ware proportion is high through the method for utilization machine vision.Method through the utilization machine vision has reduced the effect of people in cutting process, relies on the high accuracy of camera and cutting machine, can improve greatly product yield rate, reduce cost, increase work efficiency.
Technical scheme: for solving the problems of the technologies described above; The present invention provides a kind of automatic cutting method of embroidery cloth that combines with machine vision based on the DST document analysis; It is characterized in that this method uses a kind of laser cutting machine; Set up camera directly over this laser cutting machine cut surface, the automatic cutting method of said embroidery cloth comprises the steps:
(1) DST document analysis obtains original embroidery document image information and internal feature information, for images match does homework;
(2) sample extraction and processing, taking pictures through camera obtains sample image information, and sample image is carried out distortion correction, binary conversion treatment and extracts the operation of sample internal feature, obtains the characteristic information of sample;
(3) coupling is mated the DST file that obtains and the characteristic information of sample, and the matching unit barycenter also carries out the barycenter coupling according to least square method and proofreaies and correct with line of cut;
(4) DST shines upon, and the line of cut coordinate after the coupling is mapped to through coordinate transform be used for cutting under the cut surface coordinate system, exports the PLT file that laser cutting machine can be carried out then, is cut by laser cutting machine.
The present invention is input to treatment system and handles through embroidery cloth embroidery file (DST file) information that the DST analytical algorithm will be used to process down toy; Obtain matched sample; Extract through camera then and embroider cloth sample image; And utilization DST resolves the information of acquisition and cloth is embroidered in certain Processing Algorithm detection; Obtain the wherein position of each cutter unit, result is fed back to laser cutting machine carry out cutting operation, to improving cutting accuracy, reduce the work complexity, reducing workload and have very important significance.
The present invention utilizes machine vision to replace artificial method, utilizes the performance of camera resolution height, working stability, through certain handling procedure; The image processing algorithm of uses advanced can improve cutting efficiency greatly; Reduce the degree of dependence of cutting machine, raise labour productivity, because high accuracy of the present invention for the people; Can effectively improve the utilization rate of cloth, reduce the defect ware proportion of cutting.Be different from other laser cutting method based on machine vision, this method only need be taken pictures and once just can be accomplished the cutting of view picture embroidery sample, has high efficiency, characteristics that inferior rate is low.Complicacy embroidery sample there is very strong cutting power.
Description of drawings
Fig. 1 machine vision cutting flow chart
The display frame of Fig. 2 DST file;
Embroidery cloth after the corresponding DST file embroidery of Fig. 3;
The inner separate unit of Fig. 4 DST file extracts;
Fig. 5 frame extracts flow chart;
Fig. 6 DST unit and frame intersect;
Figure 79 point overflows the water completion method;
Fig. 8 is used to obtain the circular image after the cutting of transformed coordinate system;
Fig. 9 MFC operation interface;
Figure 10 laser cutting machine sketch map;
The image that goes out in the MFC interface display after Figure 11 images match;
Figure 12 line of cut location general image;
Figure 13 line of cut location topography;
Figure 14 laser cutting machine cutting process;
Figure 15 cuts the back image.
The specific embodiment
Theoretical foundation: image recognition.The first step of image recognition is to extract effective characteristics of image; Here; We mainly introduce moment characteristics amount and contour feature amount, and the moment characteristics amount comprises Hu square, normalization rotary inertia (NMI) and affine invariant moments, and the contour feature amount comprises profile discretization parameter and singular value decomposition.These 5 characteristic quantities all have good translation, rotation and constant rate property, in image object identification, have obtained using widely.
1 couple of the present invention does explanation further below in conjunction with accompanying drawing.
The 1DST document analysis
Because the embroidery file of computer design is the DST form, can not directly obtain its internal feature and image information, therefore the first step of the present invention is the DST document analysis, and the DST file is resolved, and obtains its image information and internal feature.The DST file is made up of header file and style file body, and two parts are used to deposit different information, and concrete resolving is following.
1.1DST header file is formed
The style file header mainly is used for depositing some descriptive informations about style; The DST file has the file header of one 512 byte, preceding 128 bytes with the stored in form of text some fileinfos, these information comprise the message identification and the value of information; The value of information is used decimal code; Untapped part is replaced by space character (ASCII character value 0x20), each section by character " " (ASCII character value 0x0D) isolate, specifically each section meaning is referring to table 1.
Figure BDA0000156369170000031
Table 1 DST form style file header structure
1.2 style file body structure
What deposit in the style file is the data of describing the whole needle trackings actions of style, has both comprised the displacement of every needle tracking, has also comprised the control of the actions such as trimming, colour changing of embroidery machine.The style file body of DST, form be since the 513rd byte to EOF, and per 3 bytes are used for representing a pin, and are as shown in table 2.
A 7A 6A 5A 4A 3A 2A 1A 0 B 7B 6B 5B 4B 3B 2B 1B 0 C 7C 6C 5C 4C 3C 2C 1C 0
Per three byte representation one pins in the table 2 style file
This paper arranges level and is the X forward to the right, is the Y forward vertically downward.We make Δ x, and Δ y representes the displacement of a needle tracking on X, Y direction respectively, the relative step number that promptly current pin moves on X, Y direction with respect to last needlework frame.DST is a kind of ternary coding form.Δ x, Δ y need calculate with reference to the weights shown in the table 3.
Figure BDA0000156369170000041
The weights of every correspondence in one pin of table 3.DST form
Computing formula is following:
Δ x=A 3* (9)+A 2* 9+A 1* (1)+A 0* 1+B 3* (27)+B 2* 27+B 1* (3)+B 0* 3+C 3* (81)+C 2* 81 Δ y=A 7* 1+A 6* (1)+A 5* 9+A 4* (9)+B 7* 3+B 6* (3)+B 5* 27+B 4* (27)+C 5* 81+C 4* C among (81) DST 7, C 6, C 1, C 0This four constitute its function code, as shown in table 4.
Function Value
Make C 7=C 6=0,C 1=C 0=1
Bouncing pilotage C 7=C 1=C 0=1,C 6=0
Colour changing C 7=C 6=C 1=C 0=1, represent that other position of this pin is 0
Trimming The bouncing pilotage sign indicating number that several are continuous
Finish C 7=C 6=C 5=C 4=C 1=C 0=1, represent that other position of this pin is 0
The function code of table 4DST
Also have a termination character 0xlA at DST formatted file end, in addition, empty needle is the special pin of making, and value is equal to 0.
According to said process, all data messages of DST file to be resolved, parsing is created a width of cloth blank image after accomplishing, and the information that on this image, obtains according to parsing delineates out on this blank image, thereby obtains the image information of DST file.
1.3 the unit in the justifying DST file extracts
Fig. 2 is the manufacturing DST file of the typical down toy of a width of cloth, and Fig. 3 is its corresponding embroidery cloth.The characteristic feature of this type DST file is:
1, a big outer rim is arranged in the DST file, be used for confirming to embroider the size of cloth;
2, there are some separate units inside, and each unit is the embroidered square of making down toy;
3, separate unit all has frame line separately, and this edge frame line is actual to be the line of cut of this unit;
4, be bouncing pilotage between the separate unit, do not have line to connect, perhaps have only single line to connect;
5, in order to save the space, often according to left-right symmetric, perhaps symmetry is arranged up and down between the internal element;
6, the separate unit inner element is no more than line of cut.
According to these characteristics, we have adopted method as shown in Figure 4 to extract the separate unit in the DST file.
1.4DST resolve
The parsing of DST file is formed according to the header file of DST file and is handled just passablely with coded system in theory, and still in the DST of reality file, file data tends to occur indivedual mistakes; Typical problem is exactly to represent view picture DST size+X in the header file;-X ,+Y ,-Y data are mistake often; So need carry out sorting calculation to the point among the DST, obtain actual DST image size.
At first, obtain the offset coordinates of every pin according to DST document No. mode, i.e. Δ x, Δ y value then through progressively addition, obtains the coordinate of each pin of view picture DST.Because coordinate zero point is a starting point in the DST file, for the successive image convenient processing, need handle coordinate, first on upper left side is made as coordinate zero point, be to the right x axle positive direction, be downwards y axle positive direction.When resolving, note each to the embroidery mode of operation of answering.
1.4.1 the judgement of outer rim
In general view picture is embroidered cloth all has outer rim, and embroidering the cloth housing mainly is the size that is used for confirming substantially the DST file, and product does not need outer rim but we send out existing in the reality investigation.Therefore, the first step of DST format analysis has judged whether outer rim exactly.Judge the flow process of outer rim, like Fig. 5.
In order to save cloth, some DST unit possibly intersect with outer rim, like Fig. 6 in the DST of reality embroidered square.So the size of frame not necessarily with DST space of a whole page equal and opposite in direction.Outer rim is all once embroidered by embroidery machine, so outer rim is a continuous closed data segment, and continuous data segment is very many in the DST file, therefore need carry out verification to the DST continuous data segment of collecting, and judges whether it is outer rim.Rule of judgment:
1. four end points are relevant with DST space of a whole page size;
2. the point between each end points all point-blank.
1.4.2DST the judgement of cell borders
There is following characteristic DST unit in the down toy DST file:
1, the DST cell borders is closed;
2, not thread-changing in the single DST cell borders embroidery process;
3, two adjacent frames are if close together maybe not thread-changing, generally all can thread-changing;
4, the DST unit is arranged uncertainly, and at present association area does not also have Automatic Typesetting software, all is the own random arrangement of designer, and randomness is bigger;
5, if outer rim is arranged, then the frame of DST unit is only surrounded by outer rim.If no outer rim does not then have other closed data segment to surround the DST cell borders.
Based on above characteristic, at first need confirm all closed data segments, judge then whether certain closed data segment is cell borders.Can judge according to characteristic whether a closed data segment is the DST cell borders.In practical operation, the DST cell borders is irregular figure often, judges whether inside has comparatively difficulty of element, so we adopt the processing of advancing of the method for boundary rectangle.
1.4.3DST inner element is confirmed
DST unit inner element characteristic in the down toy DST file:
1, internal element has been embroidered several times.From the consideration that reduces the colour changing number of times, generally all be that color identical in the whole space of a whole page has all been embroidered afterwards just can colour changing, so internal element will repeatedly could have been embroidered in general, so inner element comparatively disperses.
2, inner element can not surpass cell borders.
According to above characteristic, our processing method mainly is with mating except continuous data and existing DST cell borders boundary rectangle outside outer rim (if exist), the cell borders, and which element can confirm has in certain DST cell borders.
1.5 extract DST unit internal information
DST unit according to above DST document analysis obtains extracts its inner parameter, is used for next step images match.Through calculating parameters such as obtaining internal feature figure, barycenter, characteristic vector.Because might there be too much characteristic in inside, DST unit, therefore when extracting DST unit internal information, can be set to automatic information extraction, also can promptly select interesting areas by the mode of manual work extraction with mouse.The present invention tends to the latter, the better effects if of coupling some.
2 sample extraction and processing
A most important step of vision-based detection is exactly IMAQ and processing; Can realize accurate vision measurement through high-resolution camera, native system adopts Cannon 550d camera, and this camera has 1,800 ten thousand pixels; Resolution ratio is 5184*3456, and camera lens is for focusing the 50mm camera lens.Can comparatively comprehensively extract sample information through high-resolution camera, for the processing of sample image is laid a good foundation.Native system has stronger applicability, can be applied in other similar system.
2.1 system calibrating
Because the embroidery cloth full-size that will handle is 60cm*40cm, considers the lens parameters of camera, camera frame is located at 1.4m place directly over the cut surface.In case camera is in place, with the cutting machine working face of camera lens perpendicular alignmnet below, the adjustment camera is to pinpointed focus, and is locked then, no longer changes camera parameter and position.The effective field of view of camera is about 62.98cm*42cm.
Carry out camera calibration according to the Zhang Zhengyou method, can obtain the distortion parameter of camera after the demarcation and then utilize the least square circle to detect the information such as mapping point that are tied to the cutting machine coordinate system by camera coordinates.Thereby accomplish following function:
1, carries out predistortion through distortion parameter, recover the real cloth sample image of embroidering as much as possible;
2, carry out camera coordinates and be tied to the mapping under the physical coordinates system (coordinate system of machine), thereby instruct cutting machine correctly to cut.
When using for the first time, need demarcate, the distortion parameter, confidential reference items matrix and the camera coordinates that are used to obtain camera are tied to the mapping relations of cutting machine coordinate system.Calibration process is:
At first obtain the lens distortion parameter and the confidential reference items matrix of camera through " Zhang Zhengyou gridiron pattern standardization ".Preserve parameter then, behind later every acquisition piece image, at first carry out distortion correction, to recover the information of original image as far as possible.
Next, adopt " based on the coordinate system standardization of least square method circle detection " to obtain the coordinate system transformation matrix, step is following:
(1) at first designs the PLT file that is used to cut the demarcation circle, be illustrated in fig. 7 shown below, on the blank sheet of paper of a 70cm*55cm, cut out the circle of the different radii arrangement of 6*9;
(2) from the PLT file, obtain accurate central coordinate of circle under the cutting machine coordinate system, P Ij=(x Ij, y Ij), x wherein Ij, y IjX axial coordinate and the y axial coordinate of the center of circle on the cutting machine coordinate system of representing the circle of the capable j row of i respectively;
(3) utilize camera to take one and demarcate circular image clearly, utilize existing distortion parameter then, carry out image and correct;
(4) adopt casual water completion method that the image after correcting is carried out binary conversion treatment, the circle in the image is become white, background becomes black;
(5) image after the binaryzation is carried out profile and extract, detect the point sequence C that each demarcates circle Ij
(6) each point sequence is carried out the match of RANSAC circle, obtain the central coordinate of circle Q of each circle Ij=(x ' Ij, y ' Ij), x wherein Ij, y ' IjRepresent x axial coordinate and the y axial coordinate that fasten in camera coordinates in the center of circle of the circle of the capable j of i row respectively;
(7) with the central coordinate of circle under the cutting machine coordinate system according to from left to right, form from top to bottom is arranged as homogeneous coordinates matrix P, with camera coordinates system down central coordinate of circle also be shown homogeneous coordinates matrix Q according to the race-card of correspondence;
P = x 11 , y 11 , 1 x 12 , y 12 , 1 . . . x 19 , y 19 , 1 x 21 , y 21 , 1 . . . . . . Q = x ′ 11 , y ′ 11 , 1 x ′ 12 , y ′ 12 , 1 . . . x ′ 19 , y ′ 19 , 1 x ′ 21 , y ′ 21 , 1 . . . . . .
(8) adopt least square method, calculate the transform matrix M that is mapped to the cutting machine coordinate system from camera coordinate system, make it to satisfy following formula:
Q*M=P
(9) preserve matrix M, with it as later coordinate system mapping parameters.
2.2 sample extraction
The process of sample extraction is that sample is taken pictures, and carries out the process of distortion correction then.Put into when embroidering the cloth finished product at every turn and need guarantee that sample fully in the visual field of camera, prevents the situation that sample departs from the camera visual field.On the working face of cutting machine, be printed on the boundary line of workspace, the boundary line can guarantee to embroider the cloth position in valid analysing range as long as roughly align in the upper left corner when cloth was embroidered in each placement.
2.3 sample process
Shown in Figure 3 is an embroidery cloth that adopts the full-automatic computer embroidery machine to accomplish; Embroider and be covered with a lot of flower type unit (minimum unit in the sampler file) on the cloth; The position of arranging of these flower type unit is basic consistent with the DST design document; Therefore there is a perspective transformation matrix, to embroidering the cloth physical coordinates is the DST coordinate system transformation from the DST file to embroidery cloth sample.Computer embroidering machine is according to the embroidery data that comprises in the DST file, and embroidery such as execution is made, bouncing pilotage, colour changing, trimming are moved.Usually the precision of computer embroidering machine is 0.1mm, under the condition of ignoring the machine system error, can think DST file and actual embroidery cloth finished product, is man-to-man full scale mapping.In the time of on embroidering the cut surface that cloth is placed on cutting machine artificially, exists one from the DST file to the perspective transformation matrix of embroidering cloth sample image, the DST coordinate system transformation is arrived magazine embroidery cloth coordinate system.But in actual the use, it is soft yielding embroidering cloth, causes this conversion to have error.Especially when embroidering the perk of cloth part, have tangible distortion.Therefore need to adopt least square method, calculate the optimal transformation matrix.
A common colored type unit has comprised line of cut and inner a plurality of colored type elements of a closure.Arranging and the shape of these flower type elements machine of all embroider is embroidered out according to the DST file, therefore, can embroider the thorn embroidery type unit that roughly find correspondence on the cloth according to the position that obtains flower type unit in the DST file.
The basic step of sample process is:
1, cell location according to the arrange linear transformation of position and camera of DST unit, estimates the approximate location of colored type unit, orients a rectangle frame.In the position fixing process, resolve the size of the colored type unit obtain according to DST, choose a rectangle frame that can comprise colored type unit, basis draws the rectangle frame that transforms on the cutting machine by camera to the coordinate system transformation of cutting machine then.
2, binaryzation with the coloured image binaryzation in the flower type unit rectangle frame, is provided with embroidery cloth background colour and becomes black, and other elements become white, keep the contour feature of flower type unit inner element.Follow-on casual water completion method has been used in this part, is used to improve the effect that casual water is filled.A plurality of through in the embroidery sample, selecting at random as sample point; Through judging whether these points of selecting at random are background dot, be used as seed points if then keep, if not then ignoring; Increased the robustness of system after the improvement, the better effects if that the water that overflows is filled.
3, calculate the contour feature vector, calculate the Hu square and the barycenter of binaryzation frame.
2.3.1 cell location
According to the DST analysis result, can obtain the size and the corresponding bounding box of each DST unit.Also exist a kind of linear transformation between the embroidery cloth sample that DST file and camera collect, therefore can estimate each cell position of embroidering in the cloth according to the cell position that from the DST file, is resolved to.Because camera is fixed, and DST embroidery file and corresponding embroidery cloth can be regarded as basically identical.Just exist translation, rotation, three kinds of conversion of convergent-divergent between the coordinate in the DST file and the corresponding camera coordinates.
The putting position of embroidering cloth has tentatively determined shift factor T and twiddle factor R.Owing to embroider the constraint that receives to a certain degree of putting of cloth sample, promptly embroider the effective field of view that cloth must be put into camera, therefore can estimate shift factor T '.Can embroider the zoom factor S ' of cloth according to a preliminary estimate through the visual field size of camera.Four angles by embroidering cloth can estimate twiddle factor R ', and concrete steps are following:
(1) according to embroidering the position constraint that cloth is put: owing to embroider the visual field problem that need consider camera when cloth is put, native system is marked with effective coverage and orthogonal coordinate at cutting machine.To embroider cloth and substantially put into cutting machine as requested, then embroider the cloth anglec of rotation be generally less than ± 10 °.Can obtain the barycenter homogeneous coordinates V of unit, 4 summits again by DST document analysis result k=(x k, y k, 1), k=1,2,3,4, and corresponding rectangular element frame R k=W k* H kThe unit, summit is numbered 1~4 according to clockwise direction.
Parameter: x wherein kFor obtaining the x axial coordinate of k summit units centre of mass of image after the DST parsing; y kFor obtaining the y axial coordinate of k summit units centre of mass of image after the DST parsing; R kFor obtaining the frame of the unit, k summit of image after the DST parsing; W kBe its border width; H kBe its frame length.
(2) adopt the Pan and Zoom conversion coefficient that estimates, obtain the initial barycenter homogeneous coordinates of unit, 4 summits in the sample image by following formula:
V′ k=(x′ k,y′ k,1),k=1,2,3,4
The frame of unit, 4 summits in the image:
R′ k=W′ k×H′ k=S′W k×S′H k
V ′ k T = S ′ 1 0 T ′ x 0 1 T ′ y 0 0 1 V k T
Parameter: x wherein k' be the x axial coordinate of k summit units centre of mass of sample image; y k' be the y axial coordinate of k summit units centre of mass of sample image; R k' be the frame of the unit, k summit of sample image; W k' be its border width; H k' be its frame length; T ' xShift factor for x axle in the sample image; T ' yShift factor for y axle in the sample image.
(3) it is level and smooth sample image to be carried out Gauss, carry out 1/2 pyramid then and fall sampling, to the center of embroidering cloth might as well get 1/4 embroider the cloth size the rectangular area, count the highest color of the frequency of occurrences as embroidering the cloth background colour through color histogram.
(4) in sample image, with coordinate V ' kBe the center, then with 1.5W k' * 1.5H k' fill binary conversion treatment for carrying out 11 casual water in the rectangular area of length and width.Shown in Fig. 8 (wherein Fig. 8 is that 9 casual water are filled); Select 11 points as alternative seed points at first at random; To each candidate's seed points, in the zone of 11 * 11 neighborhoods, calculate color mean value, if mean value is near the background colour of embroidering cloth; And neighborhood color variance is less, then classifies this point as casual water and fills seed points.
(5) each seed points is carried out casual water filling algorithm, obtain unit V ' kBinary image.Then, carry out sliding window search, in window, calculate contour area than and regional Hu square, and with DST in corresponding vertex V kContour feature carry out similitude relatively, be shown below:
I ( A , B ) = Σ p = 1 7 | m p A - m p B m p A |
m p A = sign ( h p A ) log | h p A |
m p B = sign ( h p B ) log | h p B |
I(A,B)<T hu
Wherein: A is selected image after DST analysis unit; B sample image of the selected unit;
Figure BDA0000156369170000095
and
Figure BDA0000156369170000096
A and B, respectively, Hu moments.T HuBe Hu square similarity threshold, generally be taken as 1.5.
(6) rectangular area that will satisfy area ratio and Hu square similarity threshold is as unit V ' kThe boundary candidate frame, then, the boundary candidate that Hu square similarity is minimum is as unit V ' kThe real border frame.And obtain the true barycenter V of unit " k
(7) by vertex vector in the image Vertex vector with DST embroidery file
Figure BDA0000156369170000098
Between angle theta kAnd shift factor T ', can obtain twiddle factor estimated value R '=θ.
(8) according to resolving each DST cell borders upper left corner homogeneous coordinates L that obtains in the DST file k=(x k, y k, 1) and estimate the transformation factor obtain, can estimate the frame upper left corner homogeneous coordinates L ' of each flower type unit in the image kCorresponding DST frame scaled S ' doubly.
L ′ k T = S ′ cos θ - sin θ T x ′ sin θ cos θ T y ′ 0 0 1 L k T
2.3.2 the binaryzation of embroidery sample
After carrying out cell location, can decide the home position of each flower type unit, local positioning is carried out in each frame inside then.Not only reduce treating capacity, accelerated processing speed, and improved positioning accuracy.The binaryzation of flower type unit is the basis of accurately extracting each unit inner element contour feature.Through contrasting various binarization methods, the result of contrast binaryzation in order to guarantee the robustness of binaryzation, has improved original casual water filling algorithm, has designed a kind of adaptive casual water filling algorithm:
1, obtains the main background colour of embroidering cloth.According to DST file and camera parameter, select to embroider the cloth central area, the color histogram in computer center zone, with the highest color of frequency as embroidering cloth master color, i.e. background colour;
2, adopt 9 methods to calculate the seed points that casual water is filled.Sampling 9 points as shown in Figure 8 in image calculate whether this some place neighborhood window is background colour, if background colour is then included it in seed points;
3, adaptive threshold is chosen.Adopt basic thresholding method to obtain the threshold value that two-value is cut apart, and calculate crest, quantize the peak separation to both sides.Through the discretization of quantized interval, realize adaptive threshold;
4, with adaptive threshold the seed points that remains is overflow water and fill, and add up the coverage of each seed points and the color average of covering;
5, filter casual water blank map through hsv color, realize embroidering the appearance binaryzation.Through the seed points coverage of adding up in 9 casual water filling process, can further upgrade background colour.Calculate the hsv color value of background colour then, filter out the residual block of pixels in the binary map with this color value;
6, the UNICOM's territory area in the statistics bianry image, UNICOM's territory bounding box length-width ratio filters out the part zone errors;
7, fill the profile that remains, export complete binary map.
2.3.3 flower type element characteristic extracts
According to the cell location among the 2.3.1, regional Hu square and geometric properties in rectangle frame after the calculating embroidery unit binaryzation.
3 couplings
Calculated the internal feature of DST unit and the internal feature of colored type unit to be matched with top, next need mate.Coupling is divided into:
1, geometric properties coupling: a. comprises that area filters, and the profile that contour area is too big or too little is rejected; B. the bounding box length-width ratio is not satisfied the rejecting of threshold value.
2, outline contrasts the Hu square that each spends corresponding unit in type unit and the DST file, calculates matching result.Matching formula:
I ( A , B ) = Σ p = 1 7 | m p A - m p B m p A |
m p A = sign ( h p A ) log | h p A |
m p B = sign ( h p B ) log | h p B |
I(A,B)<T hu
And the units centre of mass of successful match remained, further do the least square conversion;
3, least square conversion, the least square conversion of each corresponding unit center-of-mass coordinate can obtain a perspective transformation matrix C among barycenter through flower type unit and the DST.
The 4DST mapping
Based on the perspective transformation matrix that coupling obtains, the line of cut that the DST document analysis is obtained is mapped on the embroidery sample image, and shows the embroidery sample image after the mapping.The present invention also has been equipped with individual fine adjustment function, if the line of cut location is inaccurate, and can manual change's line of cut position.After the DST mapping is accomplished; Preservation is mapped to the line of cut information of embroidery sample image; And this information is transformed on the cutting machine coordinate system: demarcate the transform matrix M that the camera coordinates that obtains is tied to the cutting machine coordinate system according to coordinate system; X is the line of cut coordinate of each unit among the DST, and Y is the coordinate of cutting machine coordinate system
Y=CMX
Line of cut image after the preservation conversion, this moment, this line of cut image was laser cutting machine movement locus line to the end.
Because the laser cutting machine control card is only accepted the movement locus of PLT form, the line of cut image that therefore need will obtain at last saves as the file of PLT form.
Operational instances
Be illustrated in figure 9 as the MFC interface that the present invention does, this interface mainly is divided into five parts: embroidery pattern, camera control, image detection, camera calibration and upper right corner display box.Wherein, the embroidery pattern is mainly used in the DST document analysis, through opening the DST file, shows the DST image that parses in the window thereunder; Camera control mainly is the input of control sample image, is used to obtain sample image, through showing sample information on the cutting machine at upper right corner display box; Image detection is the further processing after the sample image input, mainly is work such as images match, line of cut location; Camera calibration is when using this invention for the first time, to be used for confirming raw informations such as camera basic parameter, coordinate system transformation.
Figure 10 is the cutting machine sketch map after the improvement of the present invention.Shown in figure; Camera frame is located at 1.4m place directly over the cut surface; Can comparatively ideally obtain the cloth information of embroidering like this; Because uneven illumination is even the image post-processed there is very big influence, has therefore set up two fluorescent lamps, can reduce the inhomogeneous influence of light so to greatest extent for post-processed on the cutting machine both sides.The effective field of view of camera is about 62.98cm*42cm, therefore when placing embroidery cloth, need consider visual field problem, and we have marked the desirable visual field on cut surface, only need when cloth is embroidered in placement, put into marked region substantially and get final product.
Provide the operating procedure of an instance below:
(1) need demarcate when of the present invention for the first time using.There are two buttons to be used for demarcating in the lower right corner at MFC interface, accomplish demarcation, obtain the raw information of system through clicking these two buttons.
(2) sample of will embroidering is put on the working face of cutting machine, on working face, is printed on the boundary line of workspace, places that the boundary line can guarantee to embroider the cloth position at valid analysing range as long as roughly align in the upper left corner when embroidering cloth at every turn.
(3) click open button, the DST file that input is corresponding is with it also resolved, and in the display window of this part, shows the DST image after resolving.
(4) click " finding a view " button at the camera control section, in top-right display box, show the visual field of camera, judge through observing whether the embroidery sample is placed in the effective field of view.
(5) clicking " taking pictures " button is used for sample image is imported into system.
(6) click " position probing " button this moment, obtain the matching result of DST image and embroidery sample, shown in figure 11.Red square frame among the figure, the result of expression coupling promptly searches out characteristic area.
(7) click " line of cut detection " and obtain images displayed among Figure 12, Figure 13, the line of cut image that image obtains according to matching result, it is qualified to judge whether through the result who observes the line of cut location.
(8) judge that line of cut is qualified after, click " derivations " button and derive the PLT formatted file that cutting machine can read, begin to cut, cutting process is shown in figure 14.
(9) Figure 15 is through the cloth after the cut.

Claims (5)

1. automatic cutting method of embroidery cloth that combines with machine vision based on the DST document analysis is characterized in that this method uses a kind of laser cutting machine, has set up camera directly over this laser cutting machine cut surface, and the automatic cutting method of said embroidery cloth comprises the steps:
(1) DST document analysis obtains original embroidery document image information and internal feature information, for images match does homework;
(2) sample extraction and processing, taking pictures through camera obtains sample image information, and sample image is carried out distortion correction, binary conversion treatment and extracts the operation of sample internal feature, obtains the characteristic information of sample;
(3) coupling is mated the DST file that obtains and the characteristic information of sample, and the matching unit barycenter also carries out the barycenter coupling according to least square method and proofreaies and correct with line of cut;
(4) DST shines upon, and the line of cut coordinate after the coupling is mapped to through coordinate transform be used for cutting under the cut surface coordinate system, exports the PLT file that laser cutting machine can be carried out then, is cut by laser cutting machine.
2. the automatic cutting method of embroidery cloth that combines with machine vision based on the DST document analysis as claimed in claim 1 is characterized in that the process of DST document analysis comprises:
(1.1) resolve the function of each pin according to the coded system of DST file, the offset coordinates and the operation of writing down each pin, and the closed data segment of all appearance in the record resolving;
(1.2) resolve the result who obtains according to (1.1), create a width of cloth blank image, on image, the concrete action of each pin is delineated out, obtain DST analysis diagram picture;
(1.3) the closed data segment that obtains according to (1.1); Judge whether closed data segment is the frame of DST unit,, then extract the information of its inner information as the DST unit if should the closure data segment be bounding box; If not then continuing judgement, up to the bounding box that obtains the DST unit.
3. the automatic cutting method of embroidery cloth that combines with machine vision based on the DST document analysis as claimed in claim 1; It is characterized in that the transformation matrix that is mapped to the cutting machine coordinate system from camera coordinates system adopts " based on the coordinate system standardization of least square method circle detection " to obtain, step is following:
(1) at first designs the PLT file that is used to cut the demarcation circle;
(2) from the PLT file, obtain accurate central coordinate of circle under the cutting machine coordinate system
Figure DEST_PATH_IMAGE001
, wherein
Figure 950694DEST_PATH_IMAGE002
,
Figure DEST_PATH_IMAGE003
Represent respectively iRow jThe center of circle of circle of row is on the cutting machine coordinate system xAxial coordinate and y axial coordinate;
(3) utilize camera to take one and demarcate circular image clearly, utilize existing distortion parameter then, carry out image and correct;
(4) adopt casual water completion method that the image after correcting is carried out binary conversion treatment, the circle in the image is become white, background becomes black;
(5) image after the binaryzation is carried out profile and extract, detect the point sequence that each demarcates circle;
(6) each point sequence is carried out the match of RANSAC circle, obtain camera coordinates system and demarcate round heart coordinate down
Figure 398861DEST_PATH_IMAGE004
, wherein
Figure DEST_PATH_IMAGE005
,
Figure 631522DEST_PATH_IMAGE006
Represent respectively iRow jFasten in camera coordinates in the center of circle of the circle of row xAxial coordinate and y axial coordinate;
(7) with the central coordinate of circle under the cutting machine coordinate system according to from left to right, form from top to bottom is arranged as homogeneous coordinates matrix P, with camera coordinates system down central coordinate of circle also be arranged as homogeneous coordinates matrix Q according to the order of correspondence;
(8) adopt least square method, calculate the transform matrix M that is mapped to the cutting machine coordinate system from camera coordinates system, make it satisfied: Q*M=P.
4. the automatic cutting method of embroidery cloth that combines with machine vision based on the DST document analysis as claimed in claim 1; It is characterized in that in sample extraction and the processing procedure; Adopt the casual water completion method of improved self adaptation that sample image is carried out binary conversion treatment, promptly a plurality of as sample point through in the embroidery sample, selecting at random, judge whether these points of selecting at random are background dot; Be used as seed points if then keep, if not then ignoring.
5. the automatic cutting method of embroidery cloth that combines with machine vision based on the DST document analysis as claimed in claim 1 is characterized in that installing a fluorescent lamp respectively additional in the cutting machine both sides in order to reduce the even influence that the image post-processed is produced of uneven illumination.
CN 201210121892 2012-04-24 2012-04-24 Automatic cutting method of embroidery cloth based on combination of DST file parsing and machine vision Expired - Fee Related CN102704215B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN 201210121892 CN102704215B (en) 2012-04-24 2012-04-24 Automatic cutting method of embroidery cloth based on combination of DST file parsing and machine vision

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN 201210121892 CN102704215B (en) 2012-04-24 2012-04-24 Automatic cutting method of embroidery cloth based on combination of DST file parsing and machine vision

Publications (2)

Publication Number Publication Date
CN102704215A true CN102704215A (en) 2012-10-03
CN102704215B CN102704215B (en) 2013-09-25

Family

ID=46897249

Family Applications (1)

Application Number Title Priority Date Filing Date
CN 201210121892 Expired - Fee Related CN102704215B (en) 2012-04-24 2012-04-24 Automatic cutting method of embroidery cloth based on combination of DST file parsing and machine vision

Country Status (1)

Country Link
CN (1) CN102704215B (en)

Cited By (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107130376A (en) * 2016-02-26 2017-09-05 黄德林 Computer Three-dimensional embroidery calligraphy and painting process
CN107967697A (en) * 2017-11-23 2018-04-27 四川大学 Method for three-dimensional measurement and system based on colored random binary coding structured illumination
US10051905B2 (en) 2016-08-19 2018-08-21 Levi Strauss & Co. Laser finishing of apparel
CN108875740A (en) * 2018-06-15 2018-11-23 浙江大学 A kind of machine vision cutting method applied to laser cutting machine
CN111144160A (en) * 2019-12-27 2020-05-12 杭州爱科科技股份有限公司 Full-automatic material cutting method and device and computer readable storage medium
US10712922B2 (en) 2017-10-31 2020-07-14 Levi Strauss & Co. Laser finishing design tool with damage assets
CN111611721A (en) * 2020-05-29 2020-09-01 全球能源互联网集团有限公司 Computer arrangement method of solar cell array
CN111932491A (en) * 2020-06-23 2020-11-13 联宝(合肥)电子科技有限公司 Component detection method, device and storage medium
US11000086B2 (en) 2018-02-27 2021-05-11 Levi Strauss & Co. Apparel design system with collection management
CN113168163A (en) * 2018-11-16 2021-07-23 北面服饰公司 System and method for end-to-end item management
US11250312B2 (en) 2017-10-31 2022-02-15 Levi Strauss & Co. Garments with finishing patterns created by laser and neural network
US11313072B2 (en) 2018-02-27 2022-04-26 Levi Strauss & Co. On-demand manufacturing of laser-finished apparel
US11484080B2 (en) 2018-11-30 2022-11-01 Levi Strauss & Co. Shadow neutral 3-D garment rendering
US11530503B2 (en) 2019-07-23 2022-12-20 Levi Strauss & Co. Three-dimensional rendering preview in web-based tool for design of laser-finished garments
US11680366B2 (en) 2018-08-07 2023-06-20 Levi Strauss & Co. Laser finishing design tool

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH01289591A (en) * 1988-05-16 1989-11-21 Shinko Kogyo Co Ltd Multi head laser beam machine
JPH03138092A (en) * 1989-10-24 1991-06-12 Toshiba Corp Laser beam machine
US5555827A (en) * 1993-07-28 1996-09-17 Kabushiki Kaisha Tanabe Shishu Sewing machine including a laser cutting system, a sewing method, and an embroidering method
JPH0957473A (en) * 1995-08-25 1997-03-04 Kesami Hasegawa Method for marking identification bar code of needle
CN1145598A (en) * 1995-01-13 1997-03-19 东海工业缝纫机株式会社 Laser processing machine and sewing machine with laser processing function
EP1464435A1 (en) * 2003-04-04 2004-10-06 C.R.F. Società Consortile per Azioni Method for controlling the quality of an industrial laser process
CN2734440Y (en) * 2004-07-06 2005-10-19 东莞市粤铭激光技术有限公司 Full-automatic camera shooting brand cutting machine
DE102005050482B3 (en) * 2005-10-21 2007-01-11 Saurer Hamel Ag Continuously embroidering and cutting materials, especially appliques, in embroidering machine with laser cutting head, with cutting unit operated during frame shut-down and/or material advancement stage
CN201087267Y (en) * 2007-07-04 2008-07-16 东莞市粤铭激光技术有限公司 Multi-head computer embroidery machine with laser pattern carved device
CN201567495U (en) * 2009-08-14 2010-09-01 武汉金运激光股份有限公司 Laser cutting head and integrated laser embroidery machine using the same
CN102056704A (en) * 2008-06-16 2011-05-11 电子科学工业有限公司 Method for defining safe zones for laser machining systems

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH01289591A (en) * 1988-05-16 1989-11-21 Shinko Kogyo Co Ltd Multi head laser beam machine
JPH03138092A (en) * 1989-10-24 1991-06-12 Toshiba Corp Laser beam machine
US5555827A (en) * 1993-07-28 1996-09-17 Kabushiki Kaisha Tanabe Shishu Sewing machine including a laser cutting system, a sewing method, and an embroidering method
CN1145598A (en) * 1995-01-13 1997-03-19 东海工业缝纫机株式会社 Laser processing machine and sewing machine with laser processing function
JPH0957473A (en) * 1995-08-25 1997-03-04 Kesami Hasegawa Method for marking identification bar code of needle
EP1464435A1 (en) * 2003-04-04 2004-10-06 C.R.F. Società Consortile per Azioni Method for controlling the quality of an industrial laser process
CN2734440Y (en) * 2004-07-06 2005-10-19 东莞市粤铭激光技术有限公司 Full-automatic camera shooting brand cutting machine
DE102005050482B3 (en) * 2005-10-21 2007-01-11 Saurer Hamel Ag Continuously embroidering and cutting materials, especially appliques, in embroidering machine with laser cutting head, with cutting unit operated during frame shut-down and/or material advancement stage
CN201087267Y (en) * 2007-07-04 2008-07-16 东莞市粤铭激光技术有限公司 Multi-head computer embroidery machine with laser pattern carved device
CN102056704A (en) * 2008-06-16 2011-05-11 电子科学工业有限公司 Method for defining safe zones for laser machining systems
CN201567495U (en) * 2009-08-14 2010-09-01 武汉金运激光股份有限公司 Laser cutting head and integrated laser embroidery machine using the same

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
卞建林: "绣花机电控系统花样的代码", 《硕士论文》 *
康晓勇等: "应用于光纤电脑绣花机的激光切割系统的设计", 《工业控制计算机》 *
李泳等: "复杂轮廓激光切割路径优化算法的研究", 《天津理工大学学报》 *
钟平等: "基于机器视觉激光切割自动寻边技术研究", 《纺织高校基础科学学报》 *

Cited By (43)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107130376A (en) * 2016-02-26 2017-09-05 黄德林 Computer Three-dimensional embroidery calligraphy and painting process
US11629443B2 (en) 2016-08-19 2023-04-18 Levi Strauss & Co. Using fabric response characteristic function to create laser finishing patterns on apparel
US10980302B2 (en) 2016-08-19 2021-04-20 Levi Strauss & Co. Laser finishing of apparel
US11673419B2 (en) 2016-08-19 2023-06-13 Levi Strauss & Co. Creating a finishing pattern on a garment by laser
US10327494B2 (en) 2016-08-19 2019-06-25 Levi Strauss & Co. Laser finishing of apparel
US10470511B2 (en) 2016-08-19 2019-11-12 Levi Strauss & Co. Using laser to create finishing pattern on apparel
US11479892B2 (en) 2016-08-19 2022-10-25 Levi Strauss & Co. Laser finishing system for apparel
US10051905B2 (en) 2016-08-19 2018-08-21 Levi Strauss & Co. Laser finishing of apparel
US11384463B2 (en) 2016-08-19 2022-07-12 Levi Strauss & Co. Using laser to create finishing pattern on apparel
US11952693B2 (en) 2017-10-31 2024-04-09 Levi Strauss & Co. Using neural networks in laser finishing of apparel
US11681421B2 (en) 2017-10-31 2023-06-20 Levi Strauss & Co. Laser finishing design and preview tool
US10921968B2 (en) 2017-10-31 2021-02-16 Levi Strauss & Co. Laser finishing design tool with image preview
US10956010B2 (en) 2017-10-31 2021-03-23 Levi Strauss & Co. Laser finishing design tool with photorealistic preview of damage assets
US10712922B2 (en) 2017-10-31 2020-07-14 Levi Strauss & Co. Laser finishing design tool with damage assets
US11592974B2 (en) 2017-10-31 2023-02-28 Levi Strauss & Co. Laser finishing design tool with image preview
US11941236B2 (en) 2017-10-31 2024-03-26 Levi Strauss & Co. Tool with damage assets for laser
US11250312B2 (en) 2017-10-31 2022-02-15 Levi Strauss & Co. Garments with finishing patterns created by laser and neural network
US10891035B2 (en) 2017-10-31 2021-01-12 Levi Strauss & Co. Laser finishing design tool
CN107967697B (en) * 2017-11-23 2021-02-26 四川大学 Three-dimensional measurement method and system based on color random binary coding structure illumination
CN107967697A (en) * 2017-11-23 2018-04-27 四川大学 Method for three-dimensional measurement and system based on colored random binary coding structured illumination
US11352738B2 (en) 2018-02-27 2022-06-07 Levi Strauss & Co. On-demand manufacturing of apparel by laser finishing fabric rolls
US11618995B2 (en) 2018-02-27 2023-04-04 Levi Strauss & Co. Apparel collection management with image preview
US11702793B2 (en) 2018-02-27 2023-07-18 Levi Strauss & Co. Online ordering and manufacturing of apparel using laser-finished fabric rolls
US11697903B2 (en) 2018-02-27 2023-07-11 Levi Strauss & Co. Online ordering and just-in-time manufacturing of laser-finished garments
US11313072B2 (en) 2018-02-27 2022-04-26 Levi Strauss & Co. On-demand manufacturing of laser-finished apparel
US11000086B2 (en) 2018-02-27 2021-05-11 Levi Strauss & Co. Apparel design system with collection management
CN108875740A (en) * 2018-06-15 2018-11-23 浙江大学 A kind of machine vision cutting method applied to laser cutting machine
US11680366B2 (en) 2018-08-07 2023-06-20 Levi Strauss & Co. Laser finishing design tool
CN113168163A (en) * 2018-11-16 2021-07-23 北面服饰公司 System and method for end-to-end item management
US11899435B2 (en) 2018-11-16 2024-02-13 The North Face Apparel Corp. Systems and methods for end-to-end article management
CN113168163B (en) * 2018-11-16 2022-10-28 北面服饰公司 System and method for cut alignment
US11714399B2 (en) 2018-11-16 2023-08-01 The North Face Apparel Corp. Systems and methods for end-to-end article management
US11612203B2 (en) 2018-11-30 2023-03-28 Levi Strauss & Co. Laser finishing design tool with shadow neutral 3-D garment rendering
US11632994B2 (en) 2018-11-30 2023-04-25 Levi Strauss & Co. Laser finishing design tool with 3-D garment preview
US11925227B2 (en) 2018-11-30 2024-03-12 Levi Strauss & Co. Shadow neutral 3-D visualization of garment
US11484080B2 (en) 2018-11-30 2022-11-01 Levi Strauss & Co. Shadow neutral 3-D garment rendering
US11668036B2 (en) 2019-07-23 2023-06-06 Levi Strauss & Co. Three-dimensional rendering preview of laser-finished garments
US11530503B2 (en) 2019-07-23 2022-12-20 Levi Strauss & Co. Three-dimensional rendering preview in web-based tool for design of laser-finished garments
CN111144160B (en) * 2019-12-27 2023-10-20 杭州爱科科技股份有限公司 Full-automatic material cutting method and device and computer readable storage medium
CN111144160A (en) * 2019-12-27 2020-05-12 杭州爱科科技股份有限公司 Full-automatic material cutting method and device and computer readable storage medium
CN111611721A (en) * 2020-05-29 2020-09-01 全球能源互联网集团有限公司 Computer arrangement method of solar cell array
CN111932491A (en) * 2020-06-23 2020-11-13 联宝(合肥)电子科技有限公司 Component detection method, device and storage medium
CN111932491B (en) * 2020-06-23 2022-02-08 联宝(合肥)电子科技有限公司 Component detection method, device and storage medium

Also Published As

Publication number Publication date
CN102704215B (en) 2013-09-25

Similar Documents

Publication Publication Date Title
CN102704215B (en) Automatic cutting method of embroidery cloth based on combination of DST file parsing and machine vision
CN108549873B (en) Three-dimensional face recognition method and three-dimensional face recognition system
RU2680765C1 (en) Automated determination and cutting of non-singular contour of a picture on an image
CN101443817B (en) Method and device for determining correspondence, preferably for the three-dimensional reconstruction of a scene
CN105913093A (en) Template matching method for character recognizing and processing
CN103810491B (en) Head posture estimation interest point detection method fusing depth and gray scale image characteristic points
CN107230203A (en) Casting defect recognition methods based on human eye vision attention mechanism
CN106951905A (en) Apple identification and localization method on a kind of tree based on TOF camera
CN104200461A (en) Mutual information image selected block and sift (scale-invariant feature transform) characteristic based remote sensing image registration method
CN110287787B (en) Image recognition method, image recognition device and computer-readable storage medium
CN105913013A (en) Binocular vision face recognition algorithm
CN106127205A (en) A kind of recognition methods of the digital instrument image being applicable to indoor track machine people
CN103440035A (en) Gesture recognition system in three-dimensional space and recognition method thereof
CN102930251A (en) Two-dimensional collection data recording and discriminating device and method
CN106504262A (en) A kind of small tiles intelligent locating method of multiple features fusion
CN111161295A (en) Background stripping method for dish image
CN112016497A (en) Single-view Taijiquan action analysis and assessment system based on artificial intelligence
CN116052222A (en) Cattle face recognition method for naturally collecting cattle face image
CN108022245A (en) Photovoltaic panel template automatic generation method based on upper thread primitive correlation model
CN107194916A (en) A kind of vision measurement system of feature based Point matching
CN110348344A (en) A method of the special facial expression recognition based on two and three dimensions fusion
CN114119695A (en) Image annotation method and device and electronic equipment
CN111369497B (en) Walking type tree fruit continuous counting method and device
CN113793385A (en) Method and device for positioning fish head and fish tail
CN106709432A (en) Binocular stereoscopic vision based head detecting and counting method

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C14 Grant of patent or utility model
GR01 Patent grant
CF01 Termination of patent right due to non-payment of annual fee
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20130925

Termination date: 20170424