Neural network system for classifying fingerprints
First Claim
1. A system for classifying an unknown fingerprint image having a plurality of pixels, comprising,means for generating a pixel direction map from ridge directions found in the unknown fingerprint image;
- means for generating a coarse direction map by dividing said pixel direction map into regions and determining for each of the regions a coarse direction as a most frequent pixel direction within the region; and
a neural network classifier having an input layer of neurons connected to receive said coarse direction map and connected to a hidden layer of neurons, wherein square regions of said input layer of neurons are arranged in a plurality or rings and connected to said hidden layer of neurons, said neural network classifier further includes an output layer of neurons that represent a plurality of fingerprint classifications.
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Abstract
A system for automatically classification of human fingerprints. An unidentified fingerprint is processed to produce a direction map. The direction map is processed to generate a course direction map. The coarse direction map is input to a locally connected, highly constrained feed-forward neural network. The neural network has a highly structured architecture well-suited to exploit the rotational symmetries and asymmetries of human fingerprints. The neural network classifies the unidentified fingerprint into one of five classifications: Whorl, Double Loop, Left Loop, Right Arch and Arch.
96 Citations
10 Claims
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1. A system for classifying an unknown fingerprint image having a plurality of pixels, comprising,
means for generating a pixel direction map from ridge directions found in the unknown fingerprint image; -
means for generating a coarse direction map by dividing said pixel direction map into regions and determining for each of the regions a coarse direction as a most frequent pixel direction within the region; and a neural network classifier having an input layer of neurons connected to receive said coarse direction map and connected to a hidden layer of neurons, wherein square regions of said input layer of neurons are arranged in a plurality or rings and connected to said hidden layer of neurons, said neural network classifier further includes an output layer of neurons that represent a plurality of fingerprint classifications. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A system for classifying an unknown image having radial characteristics and a plurality of pixels, comprising,
means for generating a pixel direction map from ridge directions found in the unknown image; -
means for generating a coarse direction map by dividing said pixel direction map into regions and determining for each of the regions a coarse direction as a most frequent pixel direction within the region; and a neural network classifier having an input layer of neurons connected to receive said coarse direction map and connected to a hidden layer of neurons, wherein square regions of said input layer of neurons are arranged in a plurality or rings and connected to said hidden layer of neurons, said neural network classifier further includes an output layer of neurons that represent a plurality of fingerprint classifications.
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Specification