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Pattern Recognition of Human Fingerprint Utilizing an Efficient Artificial Intelligence Algorithm

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Signals, Machines and Automation (SIGMA 2022)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1023))

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Abstract

The fingerprint identification has great effectiveness in forensic science and helps in the criminal investigations. Fingerprints are distinctive and remain enduring throughout a person’s life. The automatic fingerprint recognition systems are dependent upon hills and its characteristics known as minutiae. Hence, it is highly essential to score these minutiae accurately then refuse the improper parts. In this work a ridge ending and ridge ramify have been utilized as minutiae for fingerprint recognition system. At the time of analysis of algorithms, the approaches of attributes impart better results. The recognition rate is increased and the error rate is diminishing with the aid of this technique. The ultimate crucial stride here in matching of automatic fingerprint is to securely extractor specifics from the binary images of captured fingerprints. There are already a variety of techniques available to extract fingerprint details. The rate of recognition for such intended approach of fingerprint recognition system using artificial neural networks is 93%. From the extricate outcome, we may infer about a very affirmative impact of artificial neural networks on the comprehensive recognition rate, specifically in low excellence images.

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Authors and Affiliations

  1. Branch of Theoretical Sciences, College of Physical Education and Sports Science, Mustansiriyah University, Baghdad, Iraq

    Nisreen Abd Alhadi Jabr

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  1. Nisreen Abd Alhadi Jabr
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Correspondence to Nisreen Abd Alhadi Jabr .

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Editors and Affiliations

  1. Department of Instrumentation and Control Engineering, Netaji Subhas University of Technology, New Delhi, Delhi, India

    Asha Rani

  2. Department of Instrumentation and Control Engineering, Netaji Subhas University of Technology, New Delhi, Delhi, India

    Bhavnesh Kumar

  3. Department of Electrical Engineering, National Institute of Technology Delhi, New Delhi, Delhi, India

    Vivek Shrivastava

  4. Department of Electrical Engineering, University of Sharjah, Sharjah, United Arab Emirates

    Ramesh C. Bansal

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Jabr, N.A.A. (2023). Pattern Recognition of Human Fingerprint Utilizing an Efficient Artificial Intelligence Algorithm. In: Rani, A., Kumar, B., Shrivastava, V., Bansal, R.C. (eds) Signals, Machines and Automation. SIGMA 2022. Lecture Notes in Electrical Engineering, vol 1023. Springer, Singapore. https://doi.org/10.1007/978-981-99-0969-8_59

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  • DOI: https://doi.org/10.1007/978-981-99-0969-8_59

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-0968-1

  • Online ISBN: 978-981-99-0969-8

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