An efficient fuzzy algorithm for aligning shapes under affine transformations
✍ Scribed by Zhong Xue; Dinggang Shen; Eam Khwang Teoh
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 205 KB
- Volume
- 34
- Category
- Article
- ISSN
- 0031-3203
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✦ Synopsis
A fuzzy algorithm for aligning object shapes under a$ne transformations is proposed in this paper. The algorithm, with the name of fuzzy alignment algorithm (FAA), extends Marques' algorithm to a$ne transformations. It can e$ciently estimate the point correspondence and the relevant a$ne transformational parameters between the feature points of the object shape and the reference shape. In this algorithm, the fuzzy point-correspondence degrees are used to describe an uncertainty point assignment, then both the parameters of the a$ne transformation and the fuzzy correspondence degrees are iteratively calculated by minimizing a constrained fuzzy objective function. To prevent FAA from sinking into local minimum when the shapes are greatly deformed, an initialization method based on a$ne invariants is designed. Comparing to the eigenvector method, the e!ectiveness and robustness of the proposed algorithm is investigated with a sensitivity study based on randomly generated points. At last, good performance of FAA is illustrated with several experiments on aligning digits and object shapes.