| Status | 已發表Published |
| Image classification using shift and scale invariant wavelet features | |
Pun C.-M.
| |
| 2005-12-01 | |
| Source Publication | WMSCI 2005 - The 9th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings
 |
| Volume | 5 |
| Pages | 279-284 |
| Abstract | An effective shift and scale invariant wavelet feature extraction method for image classification is proposed. The feature extraction process involves a normalization followed by an adaptive shift invariant wavelet packet transform. An energy signature is computed for each sub-band of these invariant wavelet coefficients. A reduced subset of energy signatures are selected as feature vector for image classification. Experimental results show that the proposed method can achieve high classification accuracy of 98.5%, and outperforms the other two image classification methods. |
| Keyword | Image classification Shift and scale invariance Shift invariance Wavelet packet transform |
| URL | View the original |
| Language | 英語English |
| Fulltext Access | |
| Document Type | Conference paper |
| Collection | DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE |
| Affiliation | Universidade de Macau |
| First Author Affilication | University of Macau |
| Recommended Citation GB/T 7714 | Pun C.-M.. Image classification using shift and scale invariant wavelet features[C], 2005, 279-284. |
| APA | Pun C.-M..(2005). Image classification using shift and scale invariant wavelet features. WMSCI 2005 - The 9th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings, 5, 279-284. |
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