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

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.