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Color Edge Detection Using Multidirectional Sobel Filter and Fuzzy Fusion

Slim Ben Chaabane1,2,*, Anas Bushnag1

1 Computer Engineering Department, Faculty of Computers and Information Technology, University of Tabuk, Tabuk 47512, Saudi Arabia
2 Electrical Engineering Department University of Tunis, CEREP, ENSIT 5 Av, Taha Hussein, 1008, Tunis, Tunisia

* Corresponding Author: Slim Ben Chaabane. Email: email

Computers, Materials & Continua 2023, 74(2), 2839-2852. https://doi.org/10.32604/cmc.2023.032760

Abstract

A new model is proposed in this paper on color edge detection that uses the second derivative operators and data fusion mechanism. The second-order neighborhood shows the connection between the current pixel and the surroundings of this pixel. This connection is for each RGB component color of the input image. Once the image edges are detected for the three primary colors: red, green, and blue, these colors are merged using the combination rule. Then, the final decision is applied to obtain the segmentation. This process allows different data sources to be combined, which is essential to improve the image information quality and have an optimal image segmentation. Finally, the segmentation results of the proposed model are validated. Moreover, the classification accuracy of the tested data is assessed, and a comparison with other current models is conducted. The comparison results show that the proposed model outperforms the existing models in image segmentation.

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Cite This Article

S. Ben Chaabane and A. Bushnag, "Color edge detection using multidirectional sobel filter and fuzzy fusion," Computers, Materials & Continua, vol. 74, no.2, pp. 2839–2852, 2023.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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