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On the Prospects of Latent MasterPrints

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Computer Vision and Image Processing (CVIP 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1567))

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Abstract

Latent fingerprints are the prime evidence for forensic officers investigating a criminal case. Subsequently, the legislative procedure considers the forensic department’s reports as authentic document to support their judgment. Hence, an automated latent fingerprint identification system must produce accurate results to ensure only culprits are punished instead of innocent individuals. Recent research confirmed the existence of a MasterPrint as a partial fingerprint identifying more than four distinct subjects enrolled with the database. Usually, latent fingerprints are partial impressions, i.e. fingerprints cover small portion of full finger. Hence, it presents a scope to examine the possibility of a Latent MasterPrint. We investigate the feasibility of the Latent MasterPrint in this article using the Multi-sensor Optical and Latent Fingerprint (MOLF) DB4 dataset. The identification results using the NIST Biometric Image Software (NBIS) reveal the possibility of Latent MasterPrints.

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Authors and Affiliations

  1. Department of Computer Science & Engineering, Indian Institute of Technology Indore, Simrol, Khandwa Road, Indore, 453552, Madhya Pradesh, India

    Mahesh Joshi, Bodhisatwa Mazumdar & Somnath Dey

Authors
  1. Mahesh Joshi
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  2. Bodhisatwa Mazumdar
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  3. Somnath Dey
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Corresponding author

Correspondence to Mahesh Joshi .

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Editors and Affiliations

  1. Indian Institute of Technology Roorkee, Roorkee, India

    Balasubramanian Raman

  2. Indian Institute of Technology Ropar, Ropar, India

    Subrahmanyam Murala

  3. Jadavpur University, Kolkata, India

    Ananda Chowdhury

  4. Indian Institute of Technology Ropar, Ropar, India

    Abhinav Dhall

  5. Indian Institute of Technology Ropar, Ropar, India

    Puneet Goyal

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Joshi, M., Mazumdar, B., Dey, S. (2022). On the Prospects of Latent MasterPrints. In: Raman, B., Murala, S., Chowdhury, A., Dhall, A., Goyal, P. (eds) Computer Vision and Image Processing. CVIP 2021. Communications in Computer and Information Science, vol 1567. Springer, Cham. https://doi.org/10.1007/978-3-031-11346-8_49

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  • DOI: https://doi.org/10.1007/978-3-031-11346-8_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-11345-1

  • Online ISBN: 978-3-031-11346-8

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