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Dynamic ROI Extraction Algorithm for Palmprints

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Advances in Swarm Intelligence (ICSI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7332))

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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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Author information

Authors and Affiliations

  1. CSE Department, Vignan University, Vadlamudi, 522213, India

    Hemantha Kumar Kalluri

  2. IDRBT, MasabTank, Hyderabad, India

    Munaga V. N. K. Prasad

  3. Department of Computer and Information Sciences, University of Hyderabad, Hyderabad, 500046, India

    Arun Agarwal

Authors
  1. Hemantha Kumar Kalluri
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  2. Munaga V. N. K. Prasad
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  3. Arun Agarwal
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Peking University, Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Shenzhen City Key Laboratory of Embedded System Design, College of Computer Science and Software Engineering, Shenzhen University, 518060, Shenzhen, China

    Zhen Ji

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© 2012 Springer-Verlag Berlin Heidelberg

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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

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31019-5

  • Online ISBN: 978-3-642-31020-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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