Identification of a Person by Palm Geometry using Invariant Features
Himanshu Maurya1, Shikha Maurya2, B. C. Sahana3
1Himanshu Maurya, Department of Electronics & Communication Engineering, National Institute of Technology, Patna (Bihar), India.
2Shikha Maurya, Department of Computer Science Engineering, ABVIIITM, Gwalior (M.P), India.
3Prof. Bikas Chandra Sahana, Department of Electonics & Communication Engineering, National Institute of Technology, Patna (Bihar), India.
Manuscript received on 10 May 2013 | Revised Manuscript received on 18 May 2013 | Manuscript Published on 30 May 2013 | PP: 264-269 | Volume-2 Issue-6, May 2013 | Retrieval Number: F0849052613/13©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Feature extraction is one of the main topics in Computer Vision. This paper presents the extraction of features of interest from two or more images of the same and different objects and the matching of these features in adjacent images. Each of these feature vectors is supposed to be distinctive and invariant to any scaling, rotation or translation of the image. It uses the SIFT (Scale Invariant Feature Transform) technique for feature extraction from the image. The paper describes our own implementation of the SIFT algorithm and highlights potential direction for future research.
Keywords: Biometric, Features, Matching, SIFT.
Scope of the Article: Computational Geometry