Color Edge Detection Using Multidirectional Sobel Filter and Fuzzy Fusion

6Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.

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.

Cite

CITATION STYLE

APA

Chaabane, S. B., & Bushnag, A. (2023). Color Edge Detection Using Multidirectional Sobel Filter and Fuzzy Fusion. Computers, Materials and Continua, 74(2), 2839–2852. https://doi.org/10.32604/cmc.2023.032760

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free