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Proceedings Paper

An accurate fuzzy edge detection method using wavelet details subimages
Author(s): Nafiseh Sedaghat; Hamidreza Pourreza
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Paper Abstract

Edge detection is a basic and important subject in computer vision and image processing. An edge detector is defined as a mathematical operator of small spatial extent that responds in some way to these discontinuities, usually classifying every image pixel as either belonging to an edge or not. Many researchers have been spent attempting to develop effective edge detection algorithms. Despite this extensive research, the task of finding the edges that correspond to true physical boundaries remains a difficult problem.Edge detection algorithms based on the application of human knowledge show their flexibility and suggest that the use of human knowledge is a reasonable alternative. In this paper we propose a fuzzy inference system with two inputs: gradient and wavelet details. First input is calculated by Sobel operator and the second is calculated by wavelet transform of input image and then reconstruction of image only with details subimages by inverse wavelet transform. There are many fuzzy edge detection methods, but none of them utilize wavelet transform as it is used in this paper. For evaluating our method, we detect edges of images with different brightness characteristics and compare results with canny edge detector. The results show the high performance of our method in finding true edges.

Paper Details

Date Published: 26 February 2010
PDF: 6 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75461Q (26 February 2010); doi: 10.1117/12.855664
Show Author Affiliations
Nafiseh Sedaghat, Islamic Azad Univ. (Iran, Islamic Republic of)
Hamidreza Pourreza, Ferdowsi Univ. (Iran, Islamic Republic of)

Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)

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