NSSC OpenIR  > 空间技术部
Template matching and registration based on edge feature
Hou, Qingyu; Lu, Lihong; Bian, Chunjiang; Zhang, Wei; Hou, Q. (houqingyu@126.com)
Department空间技术部
Source PublicationProceedings of SPIE - The International Society for Optical Engineering
2012
Language英语
ISSN0277-786X
ISBN9780819493132
AbstractIn order to improve the performance of heterogeneous image matching and registration, the Weighted Voting Accumulation Measure(WVAM) based on the edge feature and image registration algorithm based on the steepest descent of the likelihood function are proposed. The WVAM is capable of resisting the interference of noise and the similarity region and can achieve matching location of template. On this basis, the likelihood function of edge sets registration is established on the basis of Gauss Mixture Model (GMM) of point sets. In order to achieve the registration between the template and matching area, and resolve the optimum transformation parameter by using the steepest descent method, the likelihood function is regarded as objective function and the affine transformation parameter is regarded as the optimization variance. The results of simulation experiments of this algorithm proved that the good performance of template and registration. © Copyright SPIE.; In order to improve the performance of heterogeneous image matching and registration, the Weighted Voting Accumulation Measure(WVAM) based on the edge feature and image registration algorithm based on the steepest descent of the likelihood function are proposed. The WVAM is capable of resisting the interference of noise and the similarity region and can achieve matching location of template. On this basis, the likelihood function of edge sets registration is established on the basis of Gauss Mixture Model (GMM) of point sets. In order to achieve the registration between the template and matching area, and resolve the optimum transformation parameter by using the steepest descent method, the likelihood function is regarded as objective function and the affine transformation parameter is regarded as the optimization variance. The results of simulation experiments of this algorithm proved that the good performance of template and registration. © Copyright SPIE.
Conference NameOptoelectronic Imaging and Multimedia Technology II
Conference DateNovember 5, 2012 - November 7, 2012
Conference PlaceBeijing, China
Indexed ByEI
Document Type会议论文
Identifierhttp://ir.nssc.ac.cn/handle/122/2943
Collection空间技术部
Corresponding AuthorHou, Q. (houqingyu@126.com)
Recommended Citation
GB/T 7714
Hou, Qingyu,Lu, Lihong,Bian, Chunjiang,et al. Template matching and registration based on edge feature[C]:SPIE, P.O. Box 10, Bellingham, WA 98227-0010, United States,2012.
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