Title
Image classification using kernel collaborative representation with regularized least square
Abstract
Sparse representation based classification (SRC) has received much attention in computer vision and pattern recognition. SRC codes a testing sample by sparse linear combination of all the training samples and classifies the testing sample into the class with the minimum representation error. Recently, Zhang analyzes the working mechanism of SRC and points out that it is the collaborative representation but not the L1-norm sparsity that makes SRC powerful. Based on the analysis, they propose a very simple and much more efficient classification scheme, called collaborative representation based classification with regularized least square (CRC_RLS). CRC_RLS is a linear method in nature. Here we propose a kernel collaborative representation based classification with regularized least square (Kernel CRC_RLS, KCRC_RLS) by implicitly mapping the sample into high-dimensional space via kernel tricks. Our approach is highly motivated by the kernel methods which can capture the nonlinear similarity among samples and have been successfully applied in pattern recognition and machine learning. The experimental results on the CENPAMI handwritten digital database, ETH80 database, FERET face database, ORL database, AR face database, demonstrate that Kernel CRC_RLS is effective in classification, leading to promising performance.
Year
DOI
Venue
2013
10.1016/j.amc.2013.07.024
Applied Mathematics and Computation
Keywords
Field
DocType
kernel collaborative representation,efficient classification scheme,kernel crc_rls,pattern recognition,testing sample,cenpami handwritten digital database,eth80 database,feret face database,ar face database,collaborative representation,orl database,image classification,classification,src,kernel,image recognition
Kernel (linear algebra),Least squares,Linear combination,Nonlinear system,Pattern recognition,Computer science,Classification scheme,Sparse approximation,Artificial intelligence,Contextual image classification,Kernel method
Journal
Volume
ISSN
Citations 
222,
0096-3003
12
PageRank 
References 
Authors
0.49
33
5
Name
Order
Citations
PageRank
Wankou Yang153534.68
Zhenyu Wang2623.26
Jun Yin312112.32
Changyin Sun42002157.17
Karl Ricanek516518.65