2 February 2017 Underwater color image segmentation method via RGB channel fusion
Li Xuan, Zhang Mingjun
Author Affiliations +
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.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2017/$25.00 © 2017 SPIE
Li Xuan and Zhang Mingjun "Underwater color image segmentation method via RGB channel fusion," Optical Engineering 56(2), 023101 (2 February 2017). https://doi.org/10.1117/1.OE.56.2.023101
Received: 9 October 2016; Accepted: 4 January 2017; Published: 2 February 2017
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CITATIONS
Cited by 10 scholarly publications.
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KEYWORDS
Image segmentation

Image fusion

RGB color model

Image processing

Light sources and illumination

Color image segmentation

Optical engineering

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