Journal of Computer Science | |
A Novel Method for Edge Detection Using 2 Dimensional Gamma Distribution | Science Publications | |
Ali E. Zaart1  | |
关键词: Edge detection; gradient; masks construction; gamma distribution; | |
DOI : 10.3844/jcssp.2010.199.204 | |
学科分类:计算机科学(综合) | |
来源: Science Publications | |
【 摘 要 】
Problem statement: Edge detection is an important field in image processing. Edges characterize object boundaries and are therefore useful for segmentation, registration, feature extraction, and identification of objects in a scene. Approach: This study presented a novel method for edge detection using 2D Gamma distribution. Edge detection is traditionally implemented by convolving the image with masks. These masks are constructed using a first derivative, called gradient or second derivative called Laplacien. Thus, the problem of edge detection is therefore related to the problem of mask construction. We propose a novel method to construct different gradient masks from 2D Gamma distribution. Results: The different constructed masks from 2D Gamma distribution are applied on images and we obtained very good results in comparing with the well-known Sobel gradient and Canny gradient results. Conclusion:The experiment showed that the proposed method obtained very good results but with a big time complexity due to the big number of constructed masks.
【 授权许可】
Unknown
【 预 览 】
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RO201911300103611ZK.pdf | 361KB | download |