Abstract
A new blockwise collaborative representation-based classification with L2-norm of test data for accurate face recognition is presented. For training we divide images into several blocks and estimate representation coefficients of each block via L2-norm minimisation. For testing, the L2-norm of test image blocks are scaled by the trained representation coefficients. A novel classification scheme based on the L2-norm of test blocks is proposed and this scheme is jointly applied with conventional reconstruction error-based classification. Experimental results show that the proposed methods outperform other representation-based methods for face recognition.
Original language | English |
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Pages (from-to) | 1114-1116 |
Journal | Electronics Letters |
Volume | 52 |
Issue number | 13 |
Early online date | 2 Jun 2016 |
DOIs | |
Publication status | Published - 23 Jun 2016 |
Keywords
- image classification
- face recognition
- image representation
- minimisation