Title: A method of fine-grained image fuzzy main colour segmentation based on visual perception

Authors: Juanjuan Liu; Feng Gao

Addresses: Department of Information Science and Engineering, Tianshi College, Tianjin 301700, China ' School of Artificial Intelligence, Chongqing University of Arts and Sciences, Chongqing 402160, China

Abstract: In order to overcome the low segmentation accuracy of traditional main colour segmentation methods, this paper proposes a fine-grained image fuzzy main colour segmentation method based on visual perception. The colour features of fine-grained graph are optimised by using visual perception technology, and the fine-grained region features are obtained through the maximum colour link region and the surrounding colour roughness of fine-grained graph. A bilateral filter is used to enhance the details of fine-grained image, and fuzzy clustering is applied to the time-domain difference image. The edge contour of the target image is cut through the edge detection step to obtain the foreground area and complete the colour segmentation. The experimental results show that the effect of image brightness preservation is good, the segmentation accuracy is close to 100%, JS value is close to 1, and the segmentation effect is good.

Keywords: visual perception; fine-grained image; colour roughness; image foreground; main colour segmentation.

DOI: 10.1504/IJRIS.2022.125445

International Journal of Reasoning-based Intelligent Systems, 2022 Vol.14 No.2/3, pp.123 - 129

Received: 14 Sep 2021
Accepted: 07 Feb 2022

Published online: 09 Sep 2022 *

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