Abstract
2D Otsu thresholding algorithm has been proposed based on Otsu algorithm, it is more effective in image segmentation. However, the computational burden of finding optimal threshold vector is very large for 2D Otsu method. In this paper, three kinds of intelligent algorithm are applied to improve and compare the efficiency of search. Experimental results show that these methods can not only obtain the ideal segmentation results but also greatly reduce the launch time. Moreover, it is proved that the quantum particle swarm optimization (QPSO) algorithm has the highest efficiency.
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© 2014 Springer International Publishing Switzerland
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Cao, L., Ding, S., Fu, X., Chen, L. (2014). Application and Comparison of Three Intelligent Algorithms in 2D Otsu Segmentation Algorithm. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds) Advances in Swarm Intelligence. ICSI 2014. Lecture Notes in Computer Science, vol 8795. Springer, Cham. https://doi.org/10.1007/978-3-319-11897-0_26
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DOI: https://doi.org/10.1007/978-3-319-11897-0_26
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11896-3
Online ISBN: 978-3-319-11897-0
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