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.
CITATION STYLE
Cao, L., Ding, S., Fu, X., & Chen, L. (2014). Application and comparison of three intelligent algorithms in 2D otsu segmentation algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8795, pp. 221–227). Springer Verlag. https://doi.org/10.1007/978-3-319-11897-0_26
Mendeley helps you to discover research relevant for your work.