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Chinese Optics Letters

Chinese Optics Letters

| PUBLISHED MONTHLY BY CHINESE LASER PRESS AND DISTRIBUTED BY OSA

  • Vol. 9, Iss. 1 — Jan. 10, 2011
  • pp: 011001–

Point pattern matching based on kernel partial least squares

Weidong Yan, Zheng Tian, Lulu Pan, and Jinhuan Wen  »View Author Affiliations


Chinese Optics Letters, Vol. 9, Issue 1, pp. 011001- (2011)


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Abstract

Point pattern matching is an essential step in many image processing applications. This letter investigates the spectral approaches of point pattern matching, and presents a spectral feature matching algorithm based on kernel partial least squares (KPLS). Given the feature points of two images, we define position similarity matrices for the reference and sensed images, and extract the pattern vectors from the matrices using KPLS, which indicate the geometric distribution and the inner relationships of the feature points. Feature points matching are done using the bipartite graph matching method. Experiments conducted on both synthetic and real-world data demonstrate the robustness and invariance of the algorithm.

© 2011 Chinese Optics Letters

OCIS Codes
(100.0100) Image processing : Image processing
(100.2000) Image processing : Digital image processing

Citation
Weidong Yan, Zheng Tian, Lulu Pan, and Jinhuan Wen, "Point pattern matching based on kernel partial least squares," Chin. Opt. Lett. 9, 011001- (2011)
http://www.opticsinfobase.org/col/abstract.cfm?URI=col-9-1-011001

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