Underwater sea cucumber image segmentation method based on saliency and Grabcut

Abstract

The invention discloses an underwater sea cucumber image segmentation method based on significance and Grabcut, and relates to the technical field of digital image analysis and processing. The methodis characterized by comprising the following steps: defogging a collected image by using a Retinex algorithm to increase the image contrast; using an SLIC algorithm to generate a super-pixel graph, and improving the precision of target segmentation; performing target detection on the superpixel image by using a manifold sorting significance algorithm, obtaining a multi-scale significance image ofthe target through multi-scale manifold sorting, and performing weighted fusion to obtain a final significance image of the target; and combining a GrabCut algorithm with the saliency image to realizeinteractive-free segmentation of the sea cucumber target to obtain a final sea cucumber segmentation image. By means of the method, the problem that the GrabCut algorithm depends on manual participation is solved, the segmentation algorithm time is shortened, the GrabCut segmentation efficiency is improved, and automation of GrabCut underwater sea cucumber segmentation is achieved.

Description

technical field [0001] The invention relates to an image segmentation method in the field of image processing, in particular to an underwater sea cucumber image segmentation method based on saliency and Grabcut. Background technique [0002] Sea cucumbers grow on the seabed, the underwater is turbid and the topography is complicated, and they are mainly fished by hand. Personnel need to carry special equipment to dive to the seabed to work, which is inefficient and harmful to the body for a long time. In order to improve sea cucumber fishing efficiency and realize automatic fishing, it is first necessary to realize sea cucumber image segmentation in natural waters. [0003] In recent years, researchers at home and abroad have conducted in-depth research on underwater image segmentation methods. Chen et al. used the double threshold Otsu method to extract edge features, and then used the Hough transform method to segment the target edge. Lee et al. proposed an underwater t...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a kind of underwater sea cucumber image segmentation method based on saliency and Grabcut, utilize the combination of improved manifold sorting saliency detection and Grabcut algorithm, solve the problem that GrabCut algorithm relies on manual participation, reduce segmentation algorithm time, improving the accuracy of underwater target detection and increasing the efficiency of underwater sea cucumber segmentation

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