Prof. Jinli Xu Profile

Prof. Jinli Xu

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Proceedings Article | 8 June 2023 Paper

Multi-threshold laser stripe image segmentation based on improved black widow algorithm

Jinli Xu, Tianyu Liu, Jie Lu

Proceedings Volume 12707, 127074F (2023) https://doi.org/10.1117/12.2681120

KEYWORDS: Image segmentation, Image processing algorithms and systems, Mathematical optimization, Laser damage threshold, Laser applications, Image processing, Computation time, Cameras

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To solve the problems of low segmentation accuracy, mis-segmentation, and exponential increase of computation time with the rise of the number of thresholds when multi-threshold image segmentation is performed on images of multiple laser stripes in the structured lights windshield assembly detection environment, an improved black widow optimization algorithm (IBWOA) for multi-threshold laser stripe image segmentation is proposed. In the population initialization stage, Logistic chaotic mapping is used to enhance the initial population randomness. In the position updating stage, an adaptive step size strategy is introduced to improve the search speed and accuracy in the later stage, and individual variation based on the reverse learning strategy is introduced to avoid falling into local optimal solutions. Compared with existing swarm intelligence optimization algorithms, the results show that IBWOA has better search speed, accuracy, and escape ability to jump out of locally optimal solutions in multi-threshold laser stripe image segmentation.

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