Euclidean distance based fingerprint matching

  • Authors:

  • S. D. Jadhav;A. B. Barbadekar;S. P. Patil

  • Affiliations:

  • Dept of Computer Engg., Vishwakarma Institute of Technology, Pune, India;Dept of Computer Engg., Vishwakarma Institute of Technology, Pune, India;Dept.of Electronics, A.D. COE, Ashta, Sangli, India

  • Venue:
  • NEHIPISIC'11 Proceeding of 10th WSEAS international conference on electronics, hardware, wireless and optical communications, and 10th WSEAS international conference on signal processing, robotics and automation, and 3rd WSEAS international conference on nanotechnology, and 2nd WSEAS international conference on Plasma-fusion-nuclear physics
  • Year:
  • 2011

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Abstract

Forensic Science is an art and science of a print made by an impression of ridges in the skin of a finger, often used for biometric identification in criminal investigation. The law enforcement agencies uses system like AFIS (Automatic Fingerprint Identification System) where reference fingerprints are stored in database which are further used to match with latent fingerprints recovered from actual crime scene. There is high rate of rejection of latent fingerprints since they are found in damaged condition due to blood spills, oil spills, wet surface, snow, dust, etc that damages their quality and hence individuality of fingerprint is lost. Verification of such mutilated fingerprints against stored reference fingerprint can be done using Laplacian, Gaussian, minutia-based, etc methods. Each such method has there own advantages and disadvantages. The paper emphasis on the use of Gabor filters for fingerprint identification. The fingerprint matching is done by extracting the Finger code from both reference and latent fingerprints and then finding the Euclidean distance between the two corresponding finger codes. After proper training the system, the result obtained provides 99 % rate of recognition.