Freshwater fish shape detection method based on machine vision

Yingjie Wang; Zhigang Hu; ZiHan Tu; ZiJian Xu; Shangmusi Ma; Yan Chen; Ming Ma

doi:10.1117/12.2643512

9 October 2022 Freshwater fish shape detection method based on machine vision

Yingjie Wang, Zhigang Hu, ZiHan Tu, ZiJian Xu, Shangmusi Ma, Yan Chen, Ming Ma

Proceedings Volume 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022); 122461P (2022) https://doi.org/10.1117/12.2643512
Event: 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 2022, Qingdao, China

Abstract

To get the shape information of the freshwater fish in the factory environment, a freshwater fish contour detection algorithm that can resist image distortion was proposed. This method consists of three parts: distortion correction, background subtraction, and ellipse fitting. Firstly, a projection matrix of pixel points between the test image and the template image was built to correct the distortion of the image. Secondly, the ROI of the test image and template image was matched to remove the background to get the fish body image. Finally, several times of ellipse fitting method was used to ensure that the main part of the fish body was accurately fitted. The experimental results showed that the proposed algorithm can ensure the error variance within a range of 15%, greatly improving the detection accuracy in comparison to the traditional background difference and ellipse fitting algorithms.

Citation Download Citation

Yingjie Wang, Zhigang Hu, ZiHan Tu, ZiJian Xu, Shangmusi Ma, Yan Chen, and Ming Ma "Freshwater fish shape detection method based on machine vision", Proc. SPIE 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 122461P (9 October 2022); https://doi.org/10.1117/12.2643512

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