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Fingerprint classification using a feedback-based line detector.

Shesha Shah1, P S Sastry

  • 1Department of Electrical Engineering, Indian Institute of Science, Bangalore-560 012, India. shesha@ee.iisc.ernet.in

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|September 17, 2004
PubMed
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A novel algorithm accurately classifies fingerprint images into five types using a unique feature vector derived from an oriented line detector. This method captures essential orientation details for reliable fingerprint identification.

Area of Science:

  • Biometrics
  • Computer Vision
  • Pattern Recognition

Background:

  • Fingerprint classification is crucial for forensic identification and biometric systems.
  • Existing methods often struggle with complex fingerprint patterns and feature extraction.

Purpose of the Study:

  • To develop a novel algorithm for classifying fingerprint images into five standard classes.
  • To introduce a new oriented line detector and feature extraction method for improved classification accuracy.

Main Methods:

  • A novel co-operative dynamical system detects oriented lines, preserving multiple orientations.
  • Feature extraction characterizes the distribution of orientations within the fingerprint.
  • Three classifiers (SVM, nearest-neighbor, neural network) were evaluated.

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Main Results:

  • The proposed algorithm achieved high accuracy on the National Institute of Standards and Technology (NIST) fingerprint database.
  • All evaluated classifiers performed comparably, indicating the robustness of the feature extraction method.
  • The novel line detection and feature extraction effectively captured critical classification information.

Conclusions:

  • The developed fingerprint classification algorithm demonstrates high efficacy.
  • The novel oriented line detector and feature extraction process are key to the algorithm's success.
  • This approach offers a promising solution for automated fingerprint identification systems.