Research Article
An Efficient Gradient based Algorithm for Improving Performance of Image Edge Detection
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 103 - Issue 4 |
| Published: October 2014 |
| Authors: Majid Reza Vahidi, Mohammad Mansour Riahi Kashani, Alireza Bagheri |
10.5120/18060-8991
|
Majid Reza Vahidi, Mohammad Mansour Riahi Kashani, Alireza Bagheri . An Efficient Gradient based Algorithm for Improving Performance of Image Edge Detection. International Journal of Computer Applications. 103, 4 (October 2014), 7-14. DOI=10.5120/18060-8991
@article{ 10.5120/18060-8991,
author = { Majid Reza Vahidi,Mohammad Mansour Riahi Kashani,Alireza Bagheri },
title = { An Efficient Gradient based Algorithm for Improving Performance of Image Edge Detection },
journal = { International Journal of Computer Applications },
year = { 2014 },
volume = { 103 },
number = { 4 },
pages = { 7-14 },
doi = { 10.5120/18060-8991 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A Majid Reza Vahidi
%A Mohammad Mansour Riahi Kashani
%A Alireza Bagheri
%T An Efficient Gradient based Algorithm for Improving Performance of Image Edge Detection%T
%J International Journal of Computer Applications
%V 103
%N 4
%P 7-14
%R 10.5120/18060-8991
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Quality and execution time are two important factors for evaluation of edge detection algorithms. In these algorithms, there is a trade-off between quality and execution time. Some algorithms only concentrate on quality and some of them are fast and low quality. Efficient methods try to achieve high quality in a low time. This research concentrates on improvement of gradient based edge detection that is fast method and appropriate for real-time processing. The proposed algorithm reduces execution time by removing many pixels from computations. It calculates gradient and angle class of remaining pixels in a very efficient way so that it reinforces quality and locality of edges. The results of this algorithm indicated improvement of performance in comparison to Canny and LOG algorithms.
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