Title: Research on blurred edge information segmentation of image based on computer vision

Authors: Zhang Xu

Addresses: Jiangsu Institute of Commerce, Jiangsu, Nanjing 210000, China

Abstract: In the process of image fuzzy edge information segmentation by traditional methods, the segmentation effect is not ideal, the completion time is long and the accuracy is low. A fuzzy edge information segmentation method based on computer vision is proposed. After image denoising, image sharpening is carried out to extract image fuzzy edge information features. By designing a super-pixel grid, the pixels of the fuzzy edge information features of the image are matched, the inverse tensor information of the fuzzy edge of the image is analysed, and the multi-threshold values are normalised. The processing results are overlaid on the single object in the image to realise the fuzzy edge information segmentation. Experimental results show that the proposed method has better segmentation effect, shorter completion time and higher accuracy, and is of practical significance.

Keywords: computer vision; image blurring; edge information; multi-threshold segmentation.

DOI: 10.1504/IJICT.2021.113040

International Journal of Information and Communication Technology, 2021 Vol.18 No.2, pp.160 - 174

Received: 05 Sep 2019
Accepted: 15 Nov 2019
Published online: 16 Feb 2021 *

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