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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wei Jiang Kin-Man Lam Ting-Zhi Shen |
| Copyright Year | 1996 |
| Abstract | Gabor wavelets (GWs) have been commonly used for extracting local features for various applications, such as recognition, tracking, and edge detection. However, extracting the Gabor features is computationally intensive, so the features may be impractical for real-time applications. In this paper, we propose a set of simplified version of GWs (SGWs) and an efficient algorithm for extracting the features for edge detection. Experimental results show that our SGW-based edge-detection algorithm can achieve a similar performance level to that using GWs, while the runtime required for feature extraction using SGWs is faster than that with GWs with the use of the fast Fourier transform. When compared to the Canny and other conventional edge-detection methods, our proposed method can achieve a better performance in the terms of detection accuracy and computational complexity. |
| Page Count | 12 |
| File Size | 1444053 |
| Starting Page | 1036 |
| Ending Page | 1047 |
| File Format | |
| ISSN | 10834419 |
| Volume Number | 39 |
| Issue Number | 4 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-08-01 |
| Publisher Place | U.S.A. |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image edge detection Feature extraction Signal processing algorithms Discrete wavelet transforms Signal processing Gabor filters Frequency Pixel Information science Humans simplified GWs (SGWs) Edge detection Gabor wavelets (GWs) |
| Content Type | Text |
| Resource Type | Article |
| Subject | Control and Systems Engineering Information Systems Electrical and Electronic Engineering Human-Computer Interaction Computer Science Applications Software |
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