Article ID Journal Published Year Pages File Type
410844 Neurocomputing 2007 7 Pages PDF
Abstract

In this letter, a novel modular neural network (MNN) classifier, which partitions a KK-class problem into many much easier two-class problems in sub-subspaces, was proposed to perform palmprint recognition. Moreover, in order to make palmprint recognition more accurate, we introduced 2DPCA technique into the extraction of palmprint features, and removed the illumination information from the collected palm images using w/o3 technique. Our approach was compared with several existing methods, and obtained a satisfying classification performance on the Hong Kong Polytechnic University (PolyU) Palmprint Database.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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