Imaging Components, Systems, and Processing

Underwater color image segmentation method via RGB channel fusion

[+] Author Affiliations
Li Xuan, Zhang Mingjun

Harbin Engineering University, College of Mechanical and Electrical Engineering, Harbin, China

Opt. Eng. 56(2), 023101 (Feb 02, 2017). doi:10.1117/1.OE.56.2.023101
History: Received October 9, 2016; Accepted January 4, 2017
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Abstract.  Aiming at the problem of low segmentation accuracy and high computation time by applying existing segmentation methods for underwater color images, this paper has proposed an underwater color image segmentation method via RGB color channel fusion. Based on thresholding segmentation methods to conduct fast segmentation, the proposed method relies on dynamic estimation of the optimal weights for RGB channel fusion to obtain the grayscale image with high foreground-background contrast and reaches high segmentation accuracy. To verify the segmentation accuracy of the proposed method, the authors have conducted various underwater comparative experiments. The experimental results demonstrate that the proposed method is robust to illumination, and it is superior to existing methods in terms of both segmentation accuracy and computation time. Moreover, a segmentation technique is proposed for image sequences for real-time autonomous underwater vehicle operations.

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Citation

Li Xuan and Zhang Mingjun
"Underwater color image segmentation method via RGB channel fusion", Opt. Eng. 56(2), 023101 (Feb 02, 2017). ; http://dx.doi.org/10.1117/1.OE.56.2.023101


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Convolutional Oriented Boundaries: From Image Segmentation to High-Level Tasks. IEEE Trans Pattern Anal Mach Intell Published online May 02, 2017;
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