基于多阈值Otsu准则的阈值分割快速计算

doi:10.11999/JEIT160248

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Abstract

To resolve the problem of low efficiency which traditional multi-threshold Otsu existing in searching of optimal thresholds on the brute-force method, the thresholds properties of multi-threshold Otsu are analyzed, and the mathematical correspondence is proved between a set of optimal thresholds and the means of various categories. A new algorithm is proposed to calculate the optimal thresholds and a new model of searching thresholds is also built according to the properties of thresholds of multi-threshold Otsu. The algorithm searches for a set of optimal thresholds that satisfy the correspondence between the thresholds and the means of various categories segmented by them, so the optimal thresholds of Otsu can be determined. The algorithm reduces the search range effectively and optimizes the calculation of means and variances using lookup table. Experimental results show that the segmentation speed of the algorithm is greatly improved compared with the traditional multi-threshold Otsu method, and the algorithm can not only improve the computation speed, but also overcome the shortcomings of randomness and contingency of thresholds compared with other fast multi-threshold Otsu algorithm, and the results are strictly in line with the principle of multi-threshold Otsu.

Key words： Image segmentation Multi-threshold Otsu criterion Threshold selection Fast computation

Received: 17 March 2016 Published: 30 September 2016

PACS:

TP391

Fund:

The Young Scientists Fund of the National Natural Science Foundation of China (61305046), The Natural Science Foundation of Jilin Province (20140101193JC, 20150101055JC)

Corresponding Authors: CHEN Haipeng E-mail: chenhp@jlu.edu.cn

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	SHEN Xuanjing
	LIU Xiang
	CHEN Haipeng

Cite this article:

SHEN Xuanjing,LIU Xiang,CHEN Haipeng. Fast Computation of Threshold Based on Multi-threshold Otsu Criterion[J]. JEIT, 2017, 39(1): 144-149.

URL:

http://jeit.ie.ac.cn/EN/10.11999/JEIT160248 OR http://jeit.ie.ac.cn/EN/Y2017/V39/I1/144

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