Most of the Point Pattern Matching (PPM) algorithm performs poorly when the noise of the point's position and outliers exist. This paper presents a novel and robust PPM algorithm which combined Point Pair Topologi...Most of the Point Pattern Matching (PPM) algorithm performs poorly when the noise of the point's position and outliers exist. This paper presents a novel and robust PPM algorithm which combined Point Pair Topological Characteristics (PPTC) and Spectral Matching (SM) together to solve the afore mentioned issues. In which PPTC, a new shape descriptor, is firstly proposed. A new comparability measurement based on PPTC is defined as the matching probability. Finally, the correct matching results are achieved by the spectral matching method. The synthetic data experiments show its robustness by comparing with the other state-of-art algorithms and the real world data experiments show its effectiveness.展开更多
随着特高压直流输电技术飞速发展,换流阀阀基电子VBE(valve base electronics)设备的稳定性对于保障直流输电的可靠性和效率至关重要。VBE设备电路板缺陷,如短路和失效元件,直接影响直流系统稳定性,而现有的检测方法,包括人工显微镜检...随着特高压直流输电技术飞速发展,换流阀阀基电子VBE(valve base electronics)设备的稳定性对于保障直流输电的可靠性和效率至关重要。VBE设备电路板缺陷,如短路和失效元件,直接影响直流系统稳定性,而现有的检测方法,包括人工显微镜检查和自动检测算法,常受限于效率低和准确性不足。针对该问题,提出一种基于点模式匹配的自动视觉检测方法,通过生成代表关键区域的点模式并进行匹配来提高检测的效率和准确率。通过实验验证,所提方法在检测速度和准确性方面相较于传统方法有显著提升,适合于生产线上的快速质量控制,为提高直流输电设备的质量提供了有效的技术方案。展开更多
A new spectral matching algorithm is proposed by us- ing nonsubsampled contourlet transform and scale-invariant fea- ture transform. The nonsubsampled contourlet transform is used to decompose an image into a low freq...A new spectral matching algorithm is proposed by us- ing nonsubsampled contourlet transform and scale-invariant fea- ture transform. The nonsubsampled contourlet transform is used to decompose an image into a low frequency image and several high frequency images, and the scale-invariant feature transform is employed to extract feature points from the low frequency im- age. A proximity matrix is constructed for the feature points of two related images. By singular value decomposition of the proximity matrix, a matching matrix （or matching result） reflecting the match- ing degree among feature points is obtained. Experimental results indicate that the proposed algorithm can reduce time complexity and possess a higher accuracy.展开更多
Point pattern matchingisanimportantproblem inthefieldsofcomputervision and patternrecognition.In this paper,new algorithms based onirreducible matrix andrelativeinvariantfor matchingtwosets ofpoints withthe same ca...Point pattern matchingisanimportantproblem inthefieldsofcomputervision and patternrecognition.In this paper,new algorithms based onirreducible matrix andrelativeinvariantfor matchingtwosets ofpoints withthe same cardinality are proposed.Theirfundamentalideaistransformingthetwo dimensionalpointsets with n points intothe vectorsin n dimensional space. Considering these vectors as one dimensional point patterns,these new algorithms aim atreducingthe point matching problem to thatofsorting vectorsin n dimensionalspace aslong asthe sensornoise does notalterthe order ofthe elementsinthe vectors.Theoreticalanalysis and simulationresults show thatthe new algorithms are effective .展开更多
Point pattern matching (PPM) is an important topic in computer vision and pattern recog-nition . It can be widely used in many areas such as image registration, object recognition, motion de-tection, target tracking, ...Point pattern matching (PPM) is an important topic in computer vision and pattern recog-nition . It can be widely used in many areas such as image registration, object recognition, motion de-tection, target tracking, autonomous navigation, and pose estimation. This paper discusses the in-complete matching problem of two point sets under Euclidean transformation. According to geometric reasoning, some definitions for matching clique, support point pair, support index set, and support in-dex matrix, etc. are given. Based on the properties and theorems of them, a novel reasoning algo-rithm is presented, which searches for the optimal solution from top to bottom and could find out as many consistent corresponding point pairs as possible. Theoretical analysis and experimental results show that the new algorithm is very effective, and could be, under some conditions, applied to the PPM problem under other kind of transformations.展开更多
文摘Most of the Point Pattern Matching (PPM) algorithm performs poorly when the noise of the point's position and outliers exist. This paper presents a novel and robust PPM algorithm which combined Point Pair Topological Characteristics (PPTC) and Spectral Matching (SM) together to solve the afore mentioned issues. In which PPTC, a new shape descriptor, is firstly proposed. A new comparability measurement based on PPTC is defined as the matching probability. Finally, the correct matching results are achieved by the spectral matching method. The synthetic data experiments show its robustness by comparing with the other state-of-art algorithms and the real world data experiments show its effectiveness.
文摘随着特高压直流输电技术飞速发展,换流阀阀基电子VBE(valve base electronics)设备的稳定性对于保障直流输电的可靠性和效率至关重要。VBE设备电路板缺陷,如短路和失效元件,直接影响直流系统稳定性,而现有的检测方法,包括人工显微镜检查和自动检测算法,常受限于效率低和准确性不足。针对该问题,提出一种基于点模式匹配的自动视觉检测方法,通过生成代表关键区域的点模式并进行匹配来提高检测的效率和准确率。通过实验验证,所提方法在检测速度和准确性方面相较于传统方法有显著提升,适合于生产线上的快速质量控制,为提高直流输电设备的质量提供了有效的技术方案。
基金supported by the National Natural Science Foundation of China (6117212711071002)+1 种基金the Specialized Research Fund for the Doctoral Program of Higher Education (20113401110006)the Innovative Research Team of 211 Project in Anhui University (KJTD007A)
文摘A new spectral matching algorithm is proposed by us- ing nonsubsampled contourlet transform and scale-invariant fea- ture transform. The nonsubsampled contourlet transform is used to decompose an image into a low frequency image and several high frequency images, and the scale-invariant feature transform is employed to extract feature points from the low frequency im- age. A proximity matrix is constructed for the feature points of two related images. By singular value decomposition of the proximity matrix, a matching matrix （or matching result） reflecting the match- ing degree among feature points is obtained. Experimental results indicate that the proposed algorithm can reduce time complexity and possess a higher accuracy.
文摘Point pattern matchingisanimportantproblem inthefieldsofcomputervision and patternrecognition.In this paper,new algorithms based onirreducible matrix andrelativeinvariantfor matchingtwosets ofpoints withthe same cardinality are proposed.Theirfundamentalideaistransformingthetwo dimensionalpointsets with n points intothe vectorsin n dimensional space. Considering these vectors as one dimensional point patterns,these new algorithms aim atreducingthe point matching problem to thatofsorting vectorsin n dimensionalspace aslong asthe sensornoise does notalterthe order ofthe elementsinthe vectors.Theoreticalanalysis and simulationresults show thatthe new algorithms are effective .
基金This work was supported by "985" Project of Tsinghua University.
文摘Point pattern matching (PPM) is an important topic in computer vision and pattern recog-nition . It can be widely used in many areas such as image registration, object recognition, motion de-tection, target tracking, autonomous navigation, and pose estimation. This paper discusses the in-complete matching problem of two point sets under Euclidean transformation. According to geometric reasoning, some definitions for matching clique, support point pair, support index set, and support in-dex matrix, etc. are given. Based on the properties and theorems of them, a novel reasoning algo-rithm is presented, which searches for the optimal solution from top to bottom and could find out as many consistent corresponding point pairs as possible. Theoretical analysis and experimental results show that the new algorithm is very effective, and could be, under some conditions, applied to the PPM problem under other kind of transformations.
