Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
392600 | Information Sciences | 2014 | 12 Pages |
Abstract
A hand-shape based biometric identification system which is independent of the image spectrum range is proposed here. Two different spectrum ranges; visible and mid-range infrared, were used to validated the architecture, which maintained the accuracy and stability levels between ranges. In particular, three public databases were tested, obtaining accuracies over 99.9% using a 40% hold-out cross-validation approach. Discrete Hidden Markov Models (DHMM) representing each target identification class was trained with angular chain descriptors. A kernel was then extracted from the trained DHMM and applied as a feature extraction method. Finally, supervised Support Vector Machines were used to classify the extracted features.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Carlos M. Travieso, Jaime R. Ticay-Rivas, Juan C. Briceño, Marcos del Pozo-Baños, Jesús B. Alonso,