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Using Local Edge Pattern Descriptors for Edge Detection.

Authors :
Wang, Yu
Zhang, Na
Yan, Huaixin
Zuo, Min
Liu, Cuiling
Source :
International Journal of Pattern Recognition & Artificial Intelligence. Mar2018, Vol. 32 Issue 3, p-1. 16p.
Publication Year :
2018

Abstract

Edge detection is an active and critical topic in the field of image processing, and plays a vital role for some important applications such as image segmentation, pattern classification, object tracking, etc. In this paper, an edge detection approach is proposed using local edge pattern descriptor which possesses multiscale and multiresolution property, and is named varied local edge pattern (VLEP) descriptor. This method contains the following steps: firstly, Gaussian filter is used to smooth the original image. Secondly, the edge strength values, which are used to calculate the edge gradient values and can be obtained by one or more groups of VLEPs. Then, weighted fusion idea is considered when multiple groups of VLEP descriptors are used. Finally, the appropriate threshold is set to perform binarization processing on the gradient version of the image. Experimental results show that the proposed edge detection method achieved better performance than other state-of-the-art edge detection methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02180014
Volume :
32
Issue :
3
Database :
Academic Search Index
Journal :
International Journal of Pattern Recognition & Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
126397939
Full Text :
https://doi.org/10.1142/S0218001418500064