15 November 2007 Infrared image segmentation with 2D OTSU method based on particle swarm optimization
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Proceedings Volume 6787, MIPPR 2007: Multispectral Image Processing; 678717 (2007) https://doi.org/10.1117/12.749274
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
This paper proposes a global threshold selection method to do infrared image segmentation, which uses both gray-level distribution and spatial information, namely, two-dimensional OTSU method (2D OTSU). It often gets better anti-noise performance. What's more, taking consideration of the complexity of its computation, we introduce a new heuristic optimization algorithm, called the particle swarm optimization (PSO) algorithm to search the result. So an algorithm for PSO-based 2D Otsu segmentation is proposed. The experiments of segmentation the infrared images are illustrated to show that the proposed method can get ideal segmentation result with less computation cost.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Guangzhou Zhao, Guangzhou Zhao, Tianxu Zhang, Tianxu Zhang, Huazhong Xu, Huazhong Xu, } "Infrared image segmentation with 2D OTSU method based on particle swarm optimization", Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 678717 (15 November 2007); doi: 10.1117/12.749274; https://doi.org/10.1117/12.749274
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