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Title: Fingerprint feature extraction
Authors: Tin Tin Aye.
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Biometrics
Issue Date: 2003
Abstract: This dissertation focuses on extraction of minutiae from the gray fingerprint images directly without going through the usual binarization and thinning processes. Multilayer feedforward neural network is used for extraction of minutiae. Two types of most commonly used minutiae, bifurcations and ridge endings, are extracted. If the feature is not bifurcation or ridge ending, we name this image as the 'none' image class.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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