A Novel Method for Edge Detection Using 2 Dimensional Gamma Distribution
Zaart · Journal of Computer Science · 2010
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.