Fast multi-threshold Otsu algorithm with complete linear time complexity

被引:0
作者
Shen X.-J. [1 ]
Qin J. [1 ]
Lyu Y.-D. [2 ]
Wang R.-Q. [3 ]
Liu X. [1 ]
机构
[1] College of Computer Science and Technology, Jilin University, Changchun
[2] Public Computer Education and Research Center, Jilin University, Changchun
[3] The Second Hospital of Jilin University, Changchun
来源
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2019年 / 49卷 / 01期
关键词
Computer application; Fast Otsu; Image segmentation; Linear algorithm; Multi-threshold segmentation;
D O I
10.13229/j.cnki.jdxbgxb20171036
中图分类号
学科分类号
摘要
The classical multi-threshold Otsu algorithm always uses exhaustive method to find the optimal threshold value for segmenting the image, which leads to high computational complexity. With the increase in the number of thresholds, the time complexity increases exponentially. In order to solve this problem, a fast multi-threshold Otsu segmentation algorithm is proposed, which reduces the time complexity to a complete linear of O(n). This study theoretically analyze the main factors leading to the high computational complexity and time complexity in multi-threshold Otsu algorithm. Based on the above analysis, it is improved in three major aspects: numerical calculation, multi-threshold partitioning and search for optimal threshold. In the proposed algorithm, first, the numerical calculation in the segmentation process is optimized by the idea of dynamic planning. Then, the problem of multi-threshold is recursively solved, and the multi-threshold problem is decomposed into multiple single threshold problems. Finally, the multi-population PSO algorithm is used to search the optimal threshold. Experimental results show that the proposed algorithm reduces the time complexity of multi-threshold Otsu algorithm, which can be better applied in real-time environment. © 2019, Editorial Board of Jilin University. All right reserved.
引用
收藏
页码:268 / 274
页数:6
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