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A Biometric Recognition Model Based on Palm Vein Feature Characteristics

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Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1036))

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Abstract

The biometric is an automated approach to recognize a person based on unique and distinct physiological or behavioral feature characteristics. The era of biometric characteristics starts from inked palm print to iris based person recognition system. The era has been evolved to use blood vascular structure lies at palm region of hand which is found unique and distinct from person to person. The paper discuss about the proposed biometric recognition model based on the palm vein feature characteristics. The various techniques were used for enhancement, feature extraction and detection being experimented to come to a certain conclusion. The paper also discuss about the visualization and localization of blood vessel structure using Harris Stephen’s corner point detection. The recognition model is proposed to extract, detect and classify a subject based on the unique palm vein feature characteristics. This paper also includes about an interpretation of work and results comparison of proposed palm vein based biometric recognition model.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Solapur University, Solapur, India

    Shriram D. Raut

  2. School of Technology, S.R.T. M. U. N., Sub-centre Latur, Latur, India

    Vikas T. Humbe

Authors
  1. Shriram D. Raut
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  2. Vikas T. Humbe
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Corresponding author

Correspondence to Shriram D. Raut .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of South Dakota, Vermillion, SD, USA

    K. C. Santosh

  2. Solapur University, Solapur, India

    Ravindra S. Hegadi

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Raut, S.D., Humbe, V.T. (2019). A Biometric Recognition Model Based on Palm Vein Feature Characteristics. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1036. Springer, Singapore. https://doi.org/10.1007/978-981-13-9184-2_43

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  • DOI: https://doi.org/10.1007/978-981-13-9184-2_43

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9183-5

  • Online ISBN: 978-981-13-9184-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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