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Haralick Features from Wavelet Domain in Recognizing Fingerprints Using Neural Network

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Mining Intelligence and Knowledge Exploration (MIKE 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11987))

Abstract

Towards digitalization in the world, fingerprints are captured for personal identification and most of the recognitions of these captured fingerprints are having wide range of preprocessing tasks such as segmentation for extracting region of interest, enhancement for better visualization of minutiae features, orientation field estimation for fingerprint classification and minutiae matching. It is not worthy if recognition spends more time in prepocessing tasks while handling voluminous fingerprint database. Hence this work aims to recognize fingerprint without preprocessing tasks but with better accuracy and less time. In this method, wavelet co-occurrence features are extracted from approximation image of fingerprint image obtained from wavelet decomposition process and is recognized using feedforward neural network. The proposed method uses four wavelet co-occurrence features namely contrast, correlation, energy and homogeneity for recognition. The experimental results of FVC 2000, 2002 and 2004 databases show that better accuracy with less time is achieved.

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Author information

Authors and Affiliations

  1. Department of Computer Science, N.M.S.S.Vellaichamy Nadar College, Madurai, 625019, India

    K. S. Jeyalakshmi

  2. Research Centre in Computer Science, V.H.N. Senthikumara Nadar College, Virudhunagar, 626001, India

    T. Kathirvalavakumar

Authors
  1. K. S. Jeyalakshmi
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  2. T. Kathirvalavakumar
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Corresponding author

Correspondence to T. Kathirvalavakumar .

Editor information

Editors and Affiliations

  1. National Institute of Technology, Goa, India

    Purushothama B. R.

  2. National Institute of Technology, Goa, India

    Veena Thenkanidiyoor

  3. Indian Institute of Information Technology, Sri City, India

    Rajendra Prasath

  4. Indian Institute of Information Technology, Sri City, India

    Odelu Vanga

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Jeyalakshmi, K.S., Kathirvalavakumar, T. (2020). Haralick Features from Wavelet Domain in Recognizing Fingerprints Using Neural Network. In: B. R., P., Thenkanidiyoor, V., Prasath, R., Vanga, O. (eds) Mining Intelligence and Knowledge Exploration. MIKE 2019. Lecture Notes in Computer Science(), vol 11987. Springer, Cham. https://doi.org/10.1007/978-3-030-66187-8_12

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  • DOI: https://doi.org/10.1007/978-3-030-66187-8_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-66186-1

  • Online ISBN: 978-3-030-66187-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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