Enhance the alignment accuracy of active shape models using elastic graph matching

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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. © Springer-Verlag Berlin Heidelberg 2004.

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APA

Zhao, S., Gao, W., Shan, S., & Yin, B. (2004). Enhance the alignment accuracy of active shape models using elastic graph matching. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3072, 52–58. https://doi.org/10.1007/978-3-540-25948-0_8

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