Call For Paper Volume:4 Issue:10 Oct'2017 |

A Distributed Canny Edge Detector with Threshold Segmentation

Publication Date : 10/07/2015



Author(s) :

Miss. Ashwini P. Thombare , Prof. S. B. Bagal.


Conference Name :
4th International Conference on Recent Trends in Engineering & Technology(ICRTET-2015) July 2-4,2015 Organized by SNJB's KBJ College of Engineering,Chandwad,Nashik,Maharashtra,India



Abstract :

The canny edge detection is one of the most implemented edge detection algorithms because of its superior performance in noisy environment. Because of its frame level statistics, it is intensive and having high latency. Applying basic canny edge detection algorithm on input image may cause excessive edges in smooth regions and to loss of significant edges in high-detailed regions. Based on block type and the local distribution of the gradients in the image block, we present a distributed canny edge detection algorithm based on threshold segmentation that adaptively computes the edge detection thresholds. The new block-based algorithm has a significantly reduced latency and can be easily used for parallel processing applications. This paper presents improved algorithm based on threshold segmentation in which threshold of pixel in an image is estimated by calculating the mean and variance of the grayscale values of the neighbor pixels. Experimental results demonstrate that proposed algorithm can preserve more useful edge information and more robust to noise.


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