| Status | 已發表Published |
| A geometric invariant scheme for image classification | |
Pun C.-M. ; Wong C.-T.
| |
| 2005-12-01 | |
| Source Publication | Proceedings of the 2005 International Conference on Computer Vision, VISION'05
 |
| Pages | 71-77 |
| Abstract | An effective geometric invariant scheme for 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.,Wong C.-T.. A geometric invariant scheme for image classification[C], 2005, 71-77. |
| APA | Pun C.-M.., & Wong C.-T. (2005). A geometric invariant scheme for image classification. Proceedings of the 2005 International Conference on Computer Vision, VISION'05, 71-77. |
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