Open AccessStudy on Detection Image Processing Method of Offshore Cage
Author(s) -
Tianyu Gao,
Jun Jin,
Xin Xu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1769/1/012070
Subject(s) - computer vision , artificial intelligence , computer science , preprocessor , canny edge detector , image processing , edge detection , image gradient , enhanced data rates for gsm evolution , image (mathematics) , submarine pipeline , image segmentation , engineering , geotechnical engineering
The paper aims to test the integrity of offshore cages. In this paper, offshore robots are used to collect video images. Through preprocessing methods such as color space conversion and Retinex algorithm of fusion-oriented filtering, the color distortion of the image is improved and the edge information of the image is maintained, so that the collected cage image is better recognized and calculated by the computer. And the paper uses the Canny algorithm to accurately locate the edge of the image, so that the boundary information can be reflected in more detail. In this paper, the adaptive threshold segmentation algorithm combined with mathematical morphology processing method is used to segment the offshore cage image, and extract the skeleton of the decomposed image to realize the detection of the integrity of the offshore net. Finally, a ROV equipped with a camera was used to verify the proposed method in a wave-flow water tank, which confirmed the effectiveness of the method and optimized the integrity recognition and image processing of the cage.