Abstract
Region of Interest (ROI) extraction is an important task for palmprint identification. Earlier reported works used fixed size ROI for the recognition of palmprints. When the fixed size ROI is used the palm area taken up for recognition is less compared to dynamic ROI extraction. The proposed algorithm focuses on extraction of maximum possible ROI compared to existing fixed and dynamic ROI extraction techniques [7, 19]. The experimental results demonstrate that the proposed approach extracts better ROI on three databases, 1. The PolyU Palmprint Database, 2. CASIA Palmprint Image Database and 3. IIT Delhi Palmprint Database, when compared to the existing fixed size and dynamic size ROI extraction techniques.
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Kalluri, H.K., Prasad, M.V.N.K., Agarwal, A. (2012). Dynamic ROI Extraction Algorithm for Palmprints. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31020-1_26
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DOI: https://doi.org/10.1007/978-3-642-31020-1_26
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