Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
410844 | Neurocomputing | 2007 | 7 Pages |
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
Authors
Zhong-Qiu Zhao, De-Shuang Huang, Wei Jia,