## Abstract The success of contentβbased image retrieval (CBIR) relies critically on the ability to find effective image features to represent the database images. The shape of an object is a fundamental image feature and belongs to one of the most important image features used in CBIR. In this art
Image alignment based on invariant features for palmprint identification
β Scribed by Wenxin Li; David Zhang; Zhuoqun Xu
- Book ID
- 104357628
- Publisher
- Elsevier Science
- Year
- 2003
- Tongue
- English
- Weight
- 567 KB
- Volume
- 18
- Category
- Article
- ISSN
- 0923-5965
No coin nor oath required. For personal study only.
β¦ Synopsis
Palmprint identification provides a new technique for personal authentication. Previous research on palmprint identification mainly focuses on feature extraction and representation (Pattern Recognition 33(4) (1999) 691). But a crucial issue, palmprint alignment, is not addressed. Palmprint alignment involves moving and rotating the palmprints to locate at their correct position with the same direction. By this alignment operation, a certain palmprint sub-area can be easily obtained so that the corresponding palmprint feature matching will be carried out satisfactorily. In order to align palmprints, two invariant features, outer boundary direction and end point of heart line, are introduced. The key point in this paper is to propose a new automatic invariant-feature-based palmprint alignment method, which is able to deal with various image distortions such as image rotation and shift. This method provides a foundation for further feature extraction and matching. The experimental results demonstrate the effectiveness and accuracy of the proposed method.
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