The week's pick
Reseach Article
Adaptive Local Thresholding for Edge Detection
| National Conference on Advances in Technology and Applied Sciences |
| Foundation of Computer Science USA |
| NCATAS - Number 2 |
| September 2014 |
| Authors: Gaur Sanjay B.c., Jayashri Vajpai, Sandip Mehta |
| f046dc00-0a68-4eff-8a93-19d3f7031875 |
Gaur Sanjay B.c., Jayashri Vajpai, Sandip Mehta . Adaptive Local Thresholding for Edge Detection. National Conference on Advances in Technology and Applied Sciences. NCATAS, 2 (September 2014), 15-18.
Abstract
The Edge detection technique plays very important role in computer vision systems. Edges define the boundaries between different regions in an image, which helps in matching the pattern, segment, and recognize an object. In many applications the overall performance of the system depends on the proper detection of the edges such as Text Detection, Shape detection, Finger Print Recognition, Pattern Recognition etc. Hence edge detection is a fundamental aspect of low-level image processing. In this paper, a local threshold based method is proposed to detect the edge of an object. Experimental results suggest that this approach is more efficient in comparison with other traditional techniques like Prewitt, Sobel and Canny Edge detector. In order to test the performance of the proposed technique, twenty five test images have been considered. The experimental results show that the proposed method is better than the conventional techniques.
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