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Emerging ICT for Bridging the Future - Proceedings of the 49th Annual Convention of the Computer Society of India (CSI) Volume 1 pp 337–344Cite as

Learning Approach for Offline Signature Verification Using Vector Quantization Technique

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 337))

Abstract

Signature is a behavioral trait of an individual and forms a special class of handwriting in which legible letters or words may not be exhibited. Signature Verification System (SVS) can be classified as either offline or online. [1] In this paper, we used vector quantization technique for signature verification. The data is captured at a later time by using an optical scanner to convert the image into a bit pattern. The features thus extracted are said to be static. Our system is designed using cluster based features which are modeled using vector quantization as its density matching property provides improved results compared to statistical techniques. The classification ratio achieved using Vector Quantization is 67%.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Amity University Gurgaon, Gurgaon, India

    Aarti Chugh & Charu Jain

  2. Department of Electronics and Communication, Amity University Gurgaon, Gurgaon, India

    Priti Singh

  3. Department of Computer Science, JKP Polytechnic, Sonepat, India

    Preeti Rana

Authors
  1. Aarti Chugh
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  2. Charu Jain
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  3. Priti Singh
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  4. Preeti Rana
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Corresponding author

Correspondence to Aarti Chugh .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Vishakapatnam, India

    Suresh Chandra Satapathy

  2. School of Information Technology, Jawaharlal Nehru Technological University Hyderabad, Hyderabad, India

    A. Govardhan

  3. Department of CSE, CMR Technical Campus, Hyderabad, India

    K. Srujan Raju

  4. Department of Computer Science & Engineering, Faculty of Engg., Tech. & Management, University of Kalyani, Kalyani, West Bengal, India

    J. K. Mandal

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© 2015 Springer International Publishing Switzerland

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Chugh, A., Jain, C., Singh, P., Rana, P. (2015). Learning Approach for Offline Signature Verification Using Vector Quantization Technique. In: Satapathy, S., Govardhan, A., Raju, K., Mandal, J. (eds) Emerging ICT for Bridging the Future - Proceedings of the 49th Annual Convention of the Computer Society of India (CSI) Volume 1. Advances in Intelligent Systems and Computing, vol 337. Springer, Cham. https://doi.org/10.1007/978-3-319-13728-5_38

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  • DOI: https://doi.org/10.1007/978-3-319-13728-5_38

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13727-8

  • Online ISBN: 978-3-319-13728-5

  • eBook Packages: EngineeringEngineering (R0)

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