CN104515473A - Online diameter detection method of varnished wires - Google Patents

Online diameter detection method of varnished wires Download PDF

Info

Publication number
CN104515473A
CN104515473A CN201410767526.2A CN201410767526A CN104515473A CN 104515473 A CN104515473 A CN 104515473A CN 201410767526 A CN201410767526 A CN 201410767526A CN 104515473 A CN104515473 A CN 104515473A
Authority
CN
China
Prior art keywords
image
diameter
edge
gray
pixel
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.)
Pending
Application number
CN201410767526.2A
Other languages
Chinese (zh)
Inventor
郭德全
巨辉
严寒冰
谌娟娟
张芯蕊
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.)
Chengdu University of Information Technology
Chengdu Information Technology Co Ltd of CAS
Original Assignee
Chengdu Information Technology Co Ltd of CAS
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 Chengdu Information Technology Co Ltd of CAS filed Critical Chengdu Information Technology Co Ltd of CAS
Priority to CN201410767526.2A priority Critical patent/CN104515473A/en
Publication of CN104515473A publication Critical patent/CN104515473A/en
Pending legal-status Critical Current

Links

Landscapes

  • Image Analysis (AREA)

Abstract

The invention discloses an online diameter detection method of varnished wires. The online diameter detection method includes steps of acquiring diameter images of the varnished wires; filtering noise in the diameter images; subjecting the diameter images which are treated by noise filtering to edge detection to obtain edge images; calculating the diameter of the varnished wires according to the edge images. By adopting the edge detection method combining the iteration method to segment threshold of the images and the edge tracking method based on image scanning, background and target of the edge images obtained are well differentiated, edge continuity, no fake edges and burrs are generated, edge width is single pixel, and edge details are well reserved, so that the online diameter detection method has higher detection accuracy. Meanwhile, compared with a conventional edge detecting method, the edge detection method costs less time, so that the online diameter detection method has higher detection speed. In conclusion, the online diameter detection method has high theoretical value and engineering application population value.

Description

A kind of online test method of enameled wire diameter
Technical field
The invention belongs to and control and instrument field, relate to a kind of online test method to enameled wire diameter.
Background technology
Enameled wire is by conductor and insulation course a kind of winding wire dimerous.This winding wire applies one or more at conductive surface to have Ins. ulative material, and the insulator-coating thickness of functional enameled wire is directly proportional to inner conductor diameter and insulation course applies uniformly continous.Too thin or too thick insulating coating all can affect enameled wire usability.Therefore, insulating coating homogeneity, wire diameter homogeneity are one of key factors determining magnet wire insulation performance.And in the production run of enameled wire, for a certain reason, enameled wire coat may be caused to apply uneven, that is, film defect, thus affect enameled wire integral insulation performance.So in Production of Enamel Wires process, enameled wire coat coating thickness or enameled wire diameter can be measured effectively online, there is very important engineering significance.
20 years in the past, the output of China's enameled wire with per year over 10% speed increment.Expect 2015, the Production of Enamel Wires amount of China will reach 1,600,000 tons, become Production of Enamel Wires big country.But mostly be low-level repetition production phenomenon in the current Production of Enamel Wires of China, " high yield, inferior quality ", the low quality of enamelled wire that causes of magnet wire insulation performance is low.Along with manufacturing and the development of process technology and raising, requirements at the higher level are proposed to measuring accuracy and speed.Conventional measuring method, as: miking, laser measurement, CCD formation method etc. can not meet current needs.And the operating process of some of them method is loaded down with trivial details, and efficiency is low.In this case, the diameter of quick, accurate, contactless, online measurement enameled wire seems rather important.Have scholar to propose a kind of contact on-line checkingi paint film, fragile surperficial paint film, affects insulating property.There is researcher to devise enameled wire computing machine on-line monitoring system, utilize current vortex device to detect flaw indication.
Current, domestic being specifically designed to measures enameled wire diameter system also seldom, and enameled wire diameter measurement major part rests on the artificial off-line operation stage, manual measurement is to bringing very big restriction, main manifestations is: on the one hand, and manual measurement depends on the observation of people to measurement result, is subject to subjective factor impact.And reading work will be difficult to invariably allow people tired for a long time, reduce reading accuracy, measurement result will be made to produce comparatively big error, affect measurement result; On the other hand, efficiency of manual measurement is limited, for raising the efficiency, must increase operating personnel's quantity, causing cost to increase.Meanwhile, manual measurement easily causes damage to a certain degree to the paint film of enameled wire, affects enameled wire performance.
Under above technical background requirement, for improving enameled wire product quality, improve Production of Enamel Wires efficiency, reduce hand labor cost, us are facilitated to consider to adopt computer digital image treatment technology, automatic Quick Measurement is carried out to the enameled wire diameter on production line, for production scene provide accurately, advantageous information.
Summary of the invention
In order to solve the problem, the invention provides a kind of online test method of enameled wire diameter.
Technical scheme of the present invention:
An online test method for enameled wire diameter, comprises the following steps:
The diameter image of S1, collection enameled wire;
S2, noise filtering process is carried out to this diameter image, utilizes median filtering algorithm to carry out the noise of filtering diameter image, further, comprise the following steps:
S21, choose template, by the pixel of diverse location in diameter image, adopt the method for pixel traversal to make current pixel point and template center position overlap successively, preferably, adopt the template of 3*3 picture element matrix or 5*5 picture element matrix;
S22, the gray-scale value of all pixels of template covering position to be read;
S23, find out the intermediate value of these gray-scale values;
S24, the intermediate value obtained is assigned to the pixel of the current correspondence of template center, as the gray-scale value of this point;
S3, rim detection is carried out to the diameter image in step S2 after noise processed, comprises the following steps:
S31, employing process of iteration carry out Threshold segmentation to image, further, comprise the following steps:
S311, a selection initial threshold T,
T = 1 2 ( f min + f max )
F in formula minfor the minimum gradation value in image slices vegetarian refreshments, f maxfor the maximum gradation value in image slices vegetarian refreshments;
S312, application initial threshold T are to Image Segmentation Using, and according to the gray-scale value of image slices vegetarian refreshments, be two parts by Iamge Segmentation, gray-scale value is greater than the region of T and the region of the little T of gray-scale value;
The gray average u of the pixel that S313, the region calculating region and the little T of gray-scale value that gray-scale value is greater than T respectively comprise 1and u 2;
S314, calculate new threshold value T,
T = 1 2 ( u 1 + u 2 ) - - - ( 2 )
S315, repetition step S312, S313, S314, the difference of the T value calculated until double is satisfied is less than or equal to 1;
S32, Edge track carried out to the image after carrying out Threshold segmentation in step S31 obtain edge image, further, comprise the following steps:
S321, first by order scan image from left to right, finding first gray-scale value is the pixel of 1, and is labeled as A 0(i, j), wherein i, j are respectively pixel A 0horizontal ordinate and ordinate;
S322, in the direction of the clock search pixel point A 0the 3*3 neighborhood of (i, j), is decided to be new frontier point A by search first pixel identical with this pixel gray-scale value n;
If S323 is A ngray-scale value equal second frontier point A 1gray-scale value, and previous frontier point A n-1gray-scale value equal first frontier point A 0gray-scale value, then stop search, otherwise repeat step S322 continue search;
S4, the diameter image obtained according to step S3 calculate the diameter of enameled wire, further, comprise the following steps:
S41, demarcate by shooting the actual range L determining in this diameter image corresponding to a pixel 0;
S42, calculating enameled wire diameter shared pixel number n in the picture,
n=x 1-x 2
X in formula 1, x 2the horizontal ordinate that two frontier points that in image, horizontal ordinate is different are corresponding respectively;
S43, calculating enameled wire diameter L=n*L 0.
Adopt the beneficial effect of technical solution of the present invention: due to the present invention rim detection is carried out to figure time, have employed the edge detection method that process of iteration is carried out Threshold segmentation to image and combined based on the Edge track method of image scanning, thus, the edge image obtained has distinguished background and target well, and continuous edge, there is no pseudo-edge, do not have burr point to produce, border width is single pixel, better remains edge details, makes the present invention have higher accuracy of detection; Meanwhile, compared with conventional edge detection method, edge detection method of the present invention is less consuming time, makes the present invention have detection speed faster; To sum up 2 points, make the present invention have stronger theory value and engineer applied promotional value.
Accompanying drawing explanation
Fig. 1 is schematic flow sheet of the present invention;
Fig. 2 process of iteration selected threshold process flow diagram;
Fig. 3 is pixel A 0the coordinate schematic diagram of the pixel in the 3*3 neighborhood of (i, j);
Fig. 4 is the edge image adopting edge detection algorithm of the present invention to obtain;
Fig. 5 is the run time statistics of edge detection algorithm of the present invention and conventional edge detection algorithm; Sobel and Sobel rim detection run time statistics curve in figure, Robert and Robert rim detection run time statistics curve, Canny and Canny rim detection run time statistics curve, Our and rim detection run time statistics curve of the present invention;
Fig. 6 is that CCD calibrates principle schematic; In figure, 1 is lens, and 2 is linear CCD sensor, and f is the focal length of lens, and u is object distance, and v is image distance, and p is line array CCD Pixel size, the tested enameled wire diameter of L, and n is enameled wire pixel number shared by the image of imaging system on line array CCD target surface.
Embodiment
Below in conjunction with Figure of description, the invention will be further described.
As shown in Figure 1, a kind of online test method of enameled wire diameter, comprises the following steps:
The diameter image of S1, collection enameled wire;
S2, noise filtering process is carried out to this diameter image;
S3, rim detection is carried out to the diameter image in step S2 after noise filtering process, obtain edge image;
S4, calculate the diameter of enameled wire according to edge image.
Wherein, when gathering the diameter image of enameled wire in step S1, adopt line array CCD industrial camera to gather image, light source selects highlighted LED source of parallel light; When gathering enameled wire diameter image, the quality of environmental baseline and sensing element device self all can cause the generation of picture noise, because noise has randomness, unpredictability, conventional probability density function approximate description noise, to better noise rejection, known by analyzing, the noise of image mainly random noise and salt-pepper noise in the present embodiment.
Median filtering algorithm is utilized to carry out noise processed to the diameter image collected in step S2, its principle is that the pixel in neighborhood in image is sorted by gray shade scale, select middle gray-scale value to export as gray scale subsequently and be assigned to current pixel point, specifically comprise the following steps:
S21, by the pixel of diverse location in diameter image, adopt the method for pixel traversal to make current pixel point and template center position overlap successively, preferably, template adopts the template of 3*3 picture element matrix or 5*5 picture element matrix;
S22, the gray-scale value of all pixels of template covering position to be read;
S23, find out the intermediate value of these gray-scale values;
S24, the intermediate value obtained is assigned to the current pixel point of template center, as the gray-scale value of this point.
The number of the effect of medium filtering stress release treatment and the size of template and the pixel that participates in computing is in a template closely related, in underway value filtering process, template can only select one part of pixel point wherein to calculate, and reduces operand, improve computing velocity with this; From medium filtering principle, medium filtering has smoothed image effect, and its fundamental purpose eliminates isolated noise point; Medium filtering is a kind of nonlinear filtering mode, can overcome the problem of image blurring that linear filtering causes to a certain extent, have good filtration result to random noise and salt-pepper noise, better can retain the marginal information of image simultaneously.
When rim detection being carried out to the diameter image after noise filtering process in step S3, have employed the edge detection method that process of iteration is carried out Threshold segmentation to image and combined based on the Edge track method of image scanning, that is:
First, S31, employing process of iteration carry out Threshold segmentation to diameter image, as shown in Figure 2, specifically comprise the following steps when carrying out Threshold segmentation:
S311, a selection initial threshold T,
T = 1 2 ( f min + f max ) - - - ( 1 )
F in formula minfor the minimum gradation value in image slices vegetarian refreshments, f maxfor the maximum gradation value in image slices vegetarian refreshments;
S312, application initial threshold T are to Image Segmentation Using, and according to the gray-scale value of image slices vegetarian refreshments, be two parts by Iamge Segmentation, gray-scale value is greater than the region of T and the region of the little T of gray-scale value;
The gray average u of the pixel that S313, the region calculating region and the little T of gray-scale value that gray-scale value is greater than T respectively comprise 1and u 2;
S314, calculate new threshold value T,
T = 1 2 ( u 1 + u 2 ) - - - ( 2 )
S315, repetition step S312, S313, S314, the difference of the T value calculated until double is satisfied is less than or equal to 1.
Then, S32, carry out Edge track to carrying out the image after Threshold segmentation in step S31, Edge track be namely find out image border be extracted after the coordinate of marginal point, and to mark on image; Now conventional Edge track method is image scanning method, finds out the point that gray-scale value is 1, and mark corresponding coordinate by scanning entire image; Because this method needs to scan entire image, its efficiency comparison is low, and be the feature of two straight lines in conjunction with the enameled wire diameter image border collected in the present embodiment, the present invention improves on the basis of image scanning method, specifically comprises the following steps:
S321, first by order scan image from left to right, finding first gray-scale value is the pixel of 1, and is labeled as A 0(i, j), wherein i, j are respectively pixel A 0horizontal ordinate and ordinate;
S322, in the direction of the clock search pixel point A 0the 3*3 neighborhood of (i, j), A 0search first pixel identical with this pixel gray-scale value as shown in Figure 3, is decided to be new frontier point A by the coordinate of the pixel in the 3*3 neighborhood of (i, j) n;
If S323 is A ngray-scale value equal second frontier point A 1gray-scale value, and previous frontier point A n-1gray-scale value equal first frontier point A 0gray-scale value, then stop search, otherwise repeat step S322 continue search.
The edge image that edge detection method in the employing embodiment of the present invention obtains as shown in Figure 4, as can be seen from the figure the edge image obtained well has distinguished background and target, and continuous edge, there is no pseudo-edge, do not have burr point to produce, border width is single pixel, better remains edge details; Traditional edge detection algorithm has Sobel rim detection, Robert rim detection and Canny rim detection, compared with edge detection algorithm of the present invention, edge detection algorithm of the present invention is less consuming time, as Fig. 5,5 times are tested respectively to above-mentioned often kind algorithm, get its mean value, as we know from the figure, Canny rim detection is the highest 11s that is about consuming time on average, next is Robert rim detection and Sobel rim detection, both are average is consuming timely closely about 3s, and the edge detection algorithm of the present invention 0.33s that is only consuming time, greatly reduce working time.Utilize edge image can calculate enameled wire diameter.
The diameter of enameled wire is calculated in step S4, according to principle be: utilize the directional light of homogenous diffusion from back side illuminaton enameled wire, enameled wire through optical system imaging on CCD industrial camera sensor, imaging size is multiplied by a coefficient determined by optical system, be the physical size of enameled wire, as shown in Figure 6
Obtain according to imaging formula:
1 u + 1 v = 1 f - - - ( 3 )
β = v u = np L - - - ( 4 )
In formula (3), f is the focal length of lens, u is object distance, v is image distance, in formula (4), β is lens enlargement ratio, p is line array CCD Pixel size, the tested enameled wire diameter of L, n is enameled wire pixel number shared by the image of imaging system on line array CCD target surface, can obtain tested enameled wire diameter L by formula (3) and formula (4):
L = np β = ( u f - 1 ) · n · p - - - ( 5 )
As can be seen from formula (5), because u, f, p determine when design of measuring system, in fact enameled wire diameter becomes enameled wire pixel number shared by the image of imaging system on line array CCD target surface, i.e. n size, and determining that two edges of tested enameled wire can calculate n, CCD measures identification and the counting that the question variation of diameter is enameled wire diameter image border thus.
Concrete, the diameter calculating enameled wire comprises the following steps:
S41, demarcate by shooting the actual range L determining in edge image corresponding to a pixel 0:
The pixel dimension size of the line array CCD adopted in the present embodiment is H4.7 × V4.7um, in order to the measuring accuracy that improves system adds the sleeve that can be used for the spacing of adjustable lens and camera, according to imaging formula when the Hardware Design enlargement factor and the enameled wire clear picture degree collected, determine the object distance u=128mm of native system, image distance v=240mm;
After determining video camera and distance of camera lens (image distance) and camera lens and enameled wire distance (object distance), adopt the high-precision calibrating block of 3mm, 3.5mm, 5mm, 8mm as calibrated reference respectively, according to pixel number corresponding in the physical size of punctuate block and image, finally obtain the corresponding relation of image pixel and distance, show that object actual range corresponding to a pixel in native system image is L 0=0.0025mm.
Pixel number n shared by enameled wire diameter in S42, edge calculation image,
n=x 1-x 2
X in formula 1, x 2the horizontal ordinate of the point in edge image on two edges respectively.
S43, calculating enameled wire diameter L=n*L 0.
Present invention employs the edge detection method that process of iteration is carried out Threshold segmentation to image and combined based on the Edge track method of image scanning, therefore the edge image obtained has distinguished background and target well, and continuous edge, there is no pseudo-edge, do not have burr point to produce, border width is single pixel, better remain edge details, make the present invention have higher accuracy of detection; Meanwhile, compared with conventional edge detection method, edge detection method of the present invention is less consuming time, makes the present invention have detection speed faster; To sum up 2 points, make the present invention have stronger theory value and engineer applied promotional value.
Those of ordinary skill in the art will appreciate that, embodiment described here is to help reader understanding's principle of the present invention, should be understood to that protection scope of the present invention is not limited to so special statement and embodiment.Those of ordinary skill in the art can make various other various concrete distortion and combination of not departing from essence of the present invention according to these technology enlightenment disclosed by the invention, and these distortion and combination are still in protection scope of the present invention.

Claims (8)

1. an online test method for enameled wire diameter, is characterized in that comprising the following steps:
The diameter image of S1, collection enameled wire;
S2, noise filtering process is carried out to this diameter image;
S3, rim detection is carried out to the diameter image in step S2 after noise filtering process, obtain edge image;
S4, calculate the diameter of enameled wire according to edge image.
2. method according to claim 1, is characterized in that: be the noise utilizing median filtering algorithm to carry out filtering diameter image in step S2.
3. method according to claim 2, is characterized in that, the noise utilizing median filtering algorithm to carry out filtering diameter image specifically comprises the following steps:
S21, choose template, by the pixel of diverse location in diameter image, adopt the method for pixel traversal to make current pixel point and template center position overlap successively;
S22, the gray-scale value of all pixels of template covering position to be read;
S23, find out the intermediate value of these gray-scale values;
S24, the intermediate value obtained is assigned to the pixel of the current correspondence of template center, as the gray-scale value of this point.
4. method according to claim 3, is characterized in that: in step S21, template adopts the template of 3*3 picture element matrix or 5*5 picture element matrix.
5. method according to claim 1, is characterized in that in step S3, rim detection comprises the following steps:
S31, employing process of iteration carry out Threshold segmentation to diameter image;
S32, carrying out Edge track to carrying out the image after Threshold segmentation in step S31, namely obtaining edge image.
6. method according to claim 5, is characterized in that step S31 specifically comprises the following steps:
S311, a selection initial threshold T,
T = 1 2 ( f min + f max )
F in formula minfor the minimum gradation value in image slices vegetarian refreshments, f maxfor the maximum gradation value in image slices vegetarian refreshments;
S312, application initial threshold T are to Image Segmentation Using, and according to the gray-scale value of image slices vegetarian refreshments, be two parts by Iamge Segmentation, gray-scale value is greater than the region of T and the region of the little T of gray-scale value;
The gray average u of the pixel that S313, the region calculating region and the little T of gray-scale value that gray-scale value is greater than T respectively comprise 1and u 2;
S314, calculate new threshold value T,
T = 1 2 ( u 1 + u 2 ) ;
S315, repetition step S312, S313, S314, the difference of the T value calculated until double is satisfied is less than or equal to 1.
7. method according to claim 5, is characterized in that in step S32, Edge track comprises the following steps:
S321, first by order scan image from left to right, finding first gray-scale value is the pixel of 1, and is labeled as A 0(i, j), wherein i, j are respectively pixel A 0horizontal ordinate and ordinate;
S322, in the direction of the clock search pixel point A 0the 3*3 neighborhood of (i, j), is decided to be new frontier point An by search first pixel identical with this pixel gray-scale value;
If S323 is A ngray-scale value equal second frontier point A 1gray-scale value and previous frontier point A n-1gray-scale value equal first frontier point A 0gray-scale value, then stop search, otherwise repeat step S322 continue search.
8. method according to claim 1, is characterized in that the diameter calculating enameled wire in step S4 comprises the following steps:
S41, demarcate by shooting the actual range L determining in edge image corresponding to a pixel 0;
Pixel number n shared by enameled wire diameter in S42, edge calculation image,
n=x 1-x 2
X in formula 1, x 2the horizontal ordinate of the point in edge image on two edges respectively;
S43, calculating enameled wire diameter L=n*L 0.
CN201410767526.2A 2014-12-12 2014-12-12 Online diameter detection method of varnished wires Pending CN104515473A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201410767526.2A CN104515473A (en) 2014-12-12 2014-12-12 Online diameter detection method of varnished wires

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201410767526.2A CN104515473A (en) 2014-12-12 2014-12-12 Online diameter detection method of varnished wires

Publications (1)

Publication Number Publication Date
CN104515473A true CN104515473A (en) 2015-04-15

Family

ID=52791141

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201410767526.2A Pending CN104515473A (en) 2014-12-12 2014-12-12 Online diameter detection method of varnished wires

Country Status (1)

Country Link
CN (1) CN104515473A (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105157586A (en) * 2015-04-24 2015-12-16 北京林业大学 Method of measuring and calculating the diameter of any trunk by a photography range finding method
CN105203039A (en) * 2015-11-10 2015-12-30 山东赛特电工股份有限公司 Electromagnetic wire intelligent laser automatic diameter measurement control system
CN111968797A (en) * 2020-08-06 2020-11-20 珠海格力电工有限公司 Method and device for adjusting thickness of enameled wire paint film, storage medium and electronic equipment
CN113554854A (en) * 2021-08-02 2021-10-26 铜陵兢强电子科技股份有限公司 Enameled equipment stall alarm system
CN114877821A (en) * 2022-05-31 2022-08-09 苏州浪潮智能科技有限公司 Back drilling depth detection system and method for PCB

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1989004946A1 (en) * 1987-11-26 1989-06-01 Fardeau Jean Francois Method for measuring diameters of wires, profiles or circular parts by diffraction of light rays and device for implementing such method
CN101419058A (en) * 2008-12-15 2009-04-29 北京农业信息技术研究中心 Plant haulm diameter measurement device and measurement method based on machine vision
CN102032875A (en) * 2009-09-28 2011-04-27 王吉林 Image-processing-based cable sheath thickness measuring method
CN102147857A (en) * 2011-03-22 2011-08-10 黄晓华 Image processing method for detecting similar round by using improved hough transformation
CN102607437A (en) * 2011-01-24 2012-07-25 广东蓉胜超微线材股份有限公司 Movable online detection device and detection method of enamelled wire diameter
CN103512494A (en) * 2013-07-16 2014-01-15 宁波职业技术学院 Visual inspection system and method for scale micro changes of plant fruits

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1989004946A1 (en) * 1987-11-26 1989-06-01 Fardeau Jean Francois Method for measuring diameters of wires, profiles or circular parts by diffraction of light rays and device for implementing such method
CN101419058A (en) * 2008-12-15 2009-04-29 北京农业信息技术研究中心 Plant haulm diameter measurement device and measurement method based on machine vision
CN102032875A (en) * 2009-09-28 2011-04-27 王吉林 Image-processing-based cable sheath thickness measuring method
CN102607437A (en) * 2011-01-24 2012-07-25 广东蓉胜超微线材股份有限公司 Movable online detection device and detection method of enamelled wire diameter
CN102147857A (en) * 2011-03-22 2011-08-10 黄晓华 Image processing method for detecting similar round by using improved hough transformation
CN103512494A (en) * 2013-07-16 2014-01-15 宁波职业技术学院 Visual inspection system and method for scale micro changes of plant fruits

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
朱虹 主编: "《数字图像技术与应用》", 31 May 2011, 机械工程出版社 *
郑继刚 等: "《基于MATLAB的数字图像处理研究》", 31 December 2010, 云南大学出版社 *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105157586A (en) * 2015-04-24 2015-12-16 北京林业大学 Method of measuring and calculating the diameter of any trunk by a photography range finding method
CN105157586B (en) * 2015-04-24 2017-03-15 北京林业大学 A kind of method that photography telemetry calculates any place trunk diameter
CN105203039A (en) * 2015-11-10 2015-12-30 山东赛特电工股份有限公司 Electromagnetic wire intelligent laser automatic diameter measurement control system
CN111968797A (en) * 2020-08-06 2020-11-20 珠海格力电工有限公司 Method and device for adjusting thickness of enameled wire paint film, storage medium and electronic equipment
CN113554854A (en) * 2021-08-02 2021-10-26 铜陵兢强电子科技股份有限公司 Enameled equipment stall alarm system
CN113554854B (en) * 2021-08-02 2022-08-05 铜陵兢强电子科技股份有限公司 Enameled equipment stall alarm system
CN114877821A (en) * 2022-05-31 2022-08-09 苏州浪潮智能科技有限公司 Back drilling depth detection system and method for PCB
CN114877821B (en) * 2022-05-31 2023-09-22 苏州浪潮智能科技有限公司 Back drilling depth detection system and method for PCB

Similar Documents

Publication Publication Date Title
CN108364280B (en) Method and equipment for automatically describing structural crack and accurately measuring width
JP6620477B2 (en) Method and program for detecting cracks in concrete
CN103439342B (en) Based on the Infrared Non-destructive Testing method of thermal map temporal aspect
CN104515473A (en) Online diameter detection method of varnished wires
CN102680480A (en) Intelligent detecting method for cracks of concrete structures
CN103149087B (en) Follow-up window and digital image-based non-contact real-time strain measurement method
CN103345755A (en) Chessboard angular point sub-pixel extraction method based on Harris operator
CN101144703A (en) Article geometrical size measuring device and method based on multi-source image fusion
CN102032875A (en) Image-processing-based cable sheath thickness measuring method
Chen et al. The defect detection of 3D-printed ceramic curved surface parts with low contrast based on deep learning
CN104700395A (en) Method and system for detecting appearance crack of structure
CN110766683B (en) Pearl finish grade detection method and system
CN106770296B (en) A kind of four ball friction tests mill spot image polishing scratch deflection automatic measuring method
CN110873718A (en) Steel plate surface defect detection system and method based on machine vision
CN111415349A (en) Method for detecting polyester filament yarn based on image processing technology
CN111369484B (en) Rail profile detection method and device
CN117169086A (en) Method, medium and system for detecting construction quality of underground waterproof layer of building
CN113705564B (en) Pointer type instrument identification reading method
CN108827915B (en) Sub-pixel position obtaining method based on photoelectric sensing array for measuring refractive index
Huang et al. Crack detection of masonry structure based on thermal and visible image fusion and semantic segmentation
CN109115127A (en) A kind of sub-pix peak point extraction algorithm based on Bezier
CN111077055B (en) Chloride ion penetration depth measuring method
CN108875124B (en) Maximum value compensation algorithm for extracting peak value position of confocal axial response curve
Li et al. An efficient defect detection method for nuclear-fuel rod grooves through weakly supervised learning
CN111121637A (en) Grating displacement detection method based on pixel coding

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20150415

RJ01 Rejection of invention patent application after publication