Using fuzzy fractal features of digital images for the material surface analisys

Edge detection is an important task in image processing. There are a lot of approaches in this area: Sobel, Canny operators and others. One of the perspective techniques in image processing is the use of fuzzy logic and fuzzy sets theory. They allow us to increase processing quality by representing...

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Bibliographic Details
Published in:Journal of physics. Conference series 2018-01, Vol.944 (1), p.12094
Main Authors: Privezentsev, D.G., Zhiznyakov, A.L., Astafiev, A.V., Pugin, E.V.
Format: Article
Language:English
Subjects:
Digital imaging
Edge detection
Fuzzy logic
Fuzzy sets
Image processing
Physics
Pixels
Remote sensing
Representations
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Summary:Edge detection is an important task in image processing. There are a lot of approaches in this area: Sobel, Canny operators and others. One of the perspective techniques in image processing is the use of fuzzy logic and fuzzy sets theory. They allow us to increase processing quality by representing information in its fuzzy form. Most of the existing fuzzy image processing methods switch to fuzzy sets on very late stages, so this leads to some useful information loss. In this paper, a novel method of edge detection based on fuzzy image representation and fuzzy pixels is proposed. With this approach, we convert the image to fuzzy form on the first step. Different approaches to this conversion are described. Several membership functions for fuzzy pixel description and requirements for their form and view are given. A novel approach to edge detection based on Sobel operator and fuzzy image representation is proposed. Experimental testing of developed method was performed on remote sensing images.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/944/1/012094