Combined segmentation and Fourier descriptor-based underwater target image identification method

Abstract

The invention relates to an image segmentation and identification technology, and aims at providing a combined segmentation and Fourier descriptor-based underwater target image identification method.The method comprises the following steps of: segmenting an image by utilizing grayscale information and color information on the basis of combination of a grayscale information-based multi-threshold segmentation algorithm and a color information-based HSV space segmentation algorithm, so as to improve the segmentation correctness; and identifying the shape of a target after the segmentation is completed. According to the method, Fourier descriptors are selected to depict shape features, shape determination is carried out by adoption of feature comparison and classification, a Fourier descriptor library is established, and identification problems are converted into clustering problems, so that the method is higher in expandability when being compared with the method of directly carrying outshape identification by utilizing feature operators. By adoption of the multi-threshold segmentation algorithm and the HSV color segmentation algorithm, the method is relatively mature in development, wide in application and easy to grasp. By utilizing the Fourier descriptor library to carry out classification and identification, the method is capable of expanding a classification library conveniently and is suitable for different scenes.

Description

technical field [0001] The invention relates to image segmentation and recognition technology, in particular to the shape recognition of underwater regular targets, in particular to a method for underwater target image recognition based on a joint segmentation algorithm and a Fourier descriptor library. Background technique [0002] At this stage, in the field of marine engineering, the recognition and detection of underwater targets such as submarine optical cables, pipelines, shipwrecks, and ores require the support of underwater visual image feature extraction technology. Compared with the original objects and background of the ocean, the artificial facilities in the ocean often have regular shape characteristics. However, the underwater environment is complex, and bubbles, backgrounds, and reflections will all interfere with vision. How to select effective information from underwater images is the key. Due to the attenuation of light by seawater and the influence of var...

AI Technical Summary

Problems solved by technology

However, the existing technology has relatively harsh application conditions, low utilization of image information by segmented images, and high requirements for feature matching, which lead to problems such as incomplete or incomplete image segmentation algorithms and low degree of feature matching.

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