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Enhance the Alignment Accuracy of Active Shape Models Using Elastic Graph Matching

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Book cover Biometric Authentication (ICBA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3072))

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Abstract

Active Shape Model (ASM) is one of the most popular methods for image alignment. To improve its matching accuracy, in this paper, ASM searching method is combined with a simplified Elastic Bunch Graph Matching (EBGM) algorithm. Considering that EBGM is too time-consuming, landmarks are grouped into contour points and inner points, and inner points are further separated into several groups according to the distribution around salient features. For contour points, the original local derivative profile matching is exploited. While for every group of inner points, two pre-defined control points are searched by EBGM, and then used to adjust other points in the same group by using an affine transformation. Experimental results have shown that the proposed method greatly improves the alignment accuracy of ASM with only a little increase of time requirement since EBGM is only applied to a few control points.

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© 2004 Springer-Verlag Berlin Heidelberg

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Zhao, S., Gao, W., Shan, S., Yin, B. (2004). Enhance the Alignment Accuracy of Active Shape Models Using Elastic Graph Matching. In: Zhang, D., Jain, A.K. (eds) Biometric Authentication. ICBA 2004. Lecture Notes in Computer Science, vol 3072. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25948-0_8

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  • DOI: https://doi.org/10.1007/978-3-540-25948-0_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22146-3

  • Online ISBN: 978-3-540-25948-0

  • eBook Packages: Springer Book Archive

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