A Modified Snake Optimizer Algorithm with Otsu-based Method for Satellite Image Segmentation
Article No.: 26, Pages 1 - 7
Abstract
Image segmentation is an important step in image analysis that aims to segment regions of interest in an image by assigning a label to individual pixels sharing certain characteristics. Otsu-based method is a well-known thresholding technique that selects a threshold to segment regions by maximizing the variance between classes. Despite its advantages of considerable effectiveness and stability, its major drawback is high computational cost. This paper proposes a Modified Snake Optimizer algorithm (MSO), which can dynamically and efficiently tune Snake Optimizer (SO) parameters. To address the aforementioned drawback, MSO is applied with the Otsu threshold method (MSO-Otsu) in segmenting satellite images which helps analyze the snow-covered areas of mountain ranges in China. The experimental results show that the proposed MSO, in general, outperformed the traditional SO when applying to benchmark functions, and the proposed MSO-Otsu outperforms the traditional Otsu-based method in segmentation results and convergence time.
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December 2023
303 pages
ISBN:9798400708497
DOI:10.1145/3628454
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Published: 06 December 2023
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IAIT 2023
IAIT 2023: 13th International Conference on Advances in Information Technology
December 6 - 9, 2023
Bangkok, Thailand
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