Directional discriminant analysis based on nearest feature line

Authors:
Lijun Yan;Shu-Chuan Chu;John F. Roddick;Jeng-Shyang Pan
Affiliations:
Intelligent Control Research Center, Guangzhou Institute of Adavanced Technology, Chinese Academy of Sciences, Guangzhou, China and Department of Automatic Control and Test, Harbin Institute of Te ...;School of Computer Science, Engineering and Mathematics, Flinders University of South Australia, Adelaide, South Australia;School of Computer Science, Engineering and Mathematics, Flinders University of South Australia, Adelaide, South Australia;School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China
Venue:
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part II
Year:
2012

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Abstract

In this paper, two novel image feature extraction algorithms based on directional filter banks and nearest feature line are proposed, which are named Single Directional Feature Line Discriminant Analysis (SD-NFDA) and Multiple Directional Feature Discriminant Line Analysis (MD-NFDA). SD-NFDA and MD-NFDA extract not only the statistic feature of samples, but also the directionality feature. SD-NFDA and MD-NFDA can get higher average recognition rate with less running time than other nearest feature line based feature extraction algorithms. Experimental results confirm the advantages of SD-NFDA and MD-NFDA.