Image Edge Detection Based on Interval Type-2 Fuzzy Similarity

This paper presents a new method for edge detection of color images that is based on interval type-2 fuzzy similarity. Firstly, the noise of the image is estimated, and the image with noise higher than the threshold value is filtered out. Then this paper combines the type-2 fuzzy set theory to calcu...

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Bibliographic Details
Published in2019 3rd International Conference on Electronic Information Technology and Computer Engineering (EITCE) pp. 958 - 963
Main Authors Tang, Lili, Xie, Jialiang, Chen, Mingzhi, Xu, Chunyao, Zhang, Rui
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2019
Subjects
edge detection
Estimation
filter
Filtering theory
Fuzzy sets
Image color analysis
Image edge detection
interval type-2 fuzzy
Noise level
similarity
Wiener filters
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Summary:This paper presents a new method for edge detection of color images that is based on interval type-2 fuzzy similarity. Firstly, the noise of the image is estimated, and the image with noise higher than the threshold value is filtered out. Then this paper combines the type-2 fuzzy set theory to calculate the adjacent pixel similarity of each channel pixels in the image. After type reduction, it is divided into the edge and non-edge pixels by threshold. Compare to Sober operator, Canny operator, LOG operator and type-1 fuzzy similarity, the proposed method has a great balance noise resistance and edge detection accuracy.
DOI:10.1109/EITCE47263.2019.9094841