Proceedings Paper
Two dimension double PCA for extracting features and application based on between-class scatter matrix| Format | Member Price | Non-Member Price |
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Paper Abstract
Conventional PCA usually uses total scatter matrix as a generation matrix, and two dimension image matrices must be
transformed into vectors. In this paper, the between-class matrix generated by original image and its eigenvectors were
used to feature extracting. First we compressed the image in horizon direction using 2DPCA, then we compressed the
feature matrix in vertical direction. Thus, the dimension of features is lesser and the speed of classification is faster. At
the same time the category information is fully used and the recognition rate are improved.
Paper Details
Date Published: 29 October 2011
PDF: 5 pages
Proc. SPIE 8205, 2011 International Conference on Photonics, 3D-Imaging, and Visualization, 82050Y (29 October 2011); doi: 10.1117/12.906299
Published in SPIE Proceedings Vol. 8205:
2011 International Conference on Photonics, 3D-Imaging, and Visualization
Egui Zhu, Editor(s)
PDF: 5 pages
Proc. SPIE 8205, 2011 International Conference on Photonics, 3D-Imaging, and Visualization, 82050Y (29 October 2011); doi: 10.1117/12.906299
Show Author Affiliations
Ruiping Zhang, Taiyuan Univ. of Science and Technology (China)
Dongsheng Li, Automation Co. Taiyuan Iron & Steel Group Co., Ltd. (China)
Published in SPIE Proceedings Vol. 8205:
2011 International Conference on Photonics, 3D-Imaging, and Visualization
Egui Zhu, Editor(s)
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