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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kwok-Kei Lai Wu, P.S.Y. |
| Copyright Year | 1996 |
| Description | Author affiliation: Dept. of Manuf. Eng., City Univ. of Hong Kong, Kowloon, Hong Kong (Kwok-Kei Lai) |
| Abstract | A novel and speedy feature extraction method, called cellular feature extraction method (CFEM), is proposed in this paper. The feature extraction process is particularly important in image processing because it aims to identify all target pixels of the image. The proposed CFEM, inter alia, is particularly effective in extracting useful features of line drawings and more time-saving in processing larger-size images. The main idea behind CFEM is to ignore most of the non-target pixels which bear no useful information to the job at-hand. By design, the CFEM could selectively read out all target pixels of an image. As such, the CFEM can also act as a preprocessing method, and is fully compatible with other image processing techniques, such as filtering and thinning. When CFEM is combined with other image processing techniques to process an image, same results will be obtained in lesser time than that without CFEM. The results of experimenting CFEM in line drawings show a time-reduction of 74% in processing the largest testing image. The multiresolution properties and the limitations of CFEM are discussed. |
| Starting Page | 261 |
| Ending Page | 266 |
| File Size | 726177 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780332806 |
| ISSN | 1062922X |
| DOI | 10.1109/ICSMC.1996.569777 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1996-10-14 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Feature extraction Engineering drawings Image processing Pixel Pulp manufacturing Image resolution Digital images Hardware Object recognition Computer aided manufacturing |
| Content Type | Text |
| Resource Type | Article |
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