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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | ChangTao He WeiXing Wang |
| Copyright Year | 2010 |
| Abstract | Image segmentation has attracted the attention of researchers for many decades. Different approaches have been developed in order to find out the solution in many different segmentation situations. In this paper a novel method for rock fracture image using improved pulse coupled neural networks (PCNN) is presented. We apply progressive scan and region marked method to detect accurate edges of rock fracture images, the experiment results show that the proposed method can be used as a new image edge detection method. Compared to the traditional edge detection algorithms such as Canny operator and the other edge detection operators (e.g. vector gradient and MV), the proposed method can easily obtain the rock fracture images' orientations, curvatures, lengths, apertures and other useful information. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 285996 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424449637 |
| DOI | 10.1109/SOPO.2010.5504347 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-06-19 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image segmentation Image edge detection Image processing Neurons Neural networks Fires Artificial neural networks Mathematical model Joining processes Pixel |
| Content Type | Text |
| Resource Type | Article |
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