Fast Computation of Threshold Based on Multi-threshold Otsu Criterion

SHEN Xuanjing; LIU Xiang; CHEN Haipeng

doi:10.11999/JEIT160248

Volume 39 Issue 1

Jan. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(1): 144-149

SHEN Xuanjing, LIU Xiang, CHEN Haipeng. Fast Computation of Threshold Based on Multi-threshold Otsu Criterion[J]. Journal of Electronics & Information Technology, 2017, 39(1): 144-149. doi: 10.11999/JEIT160248

Citation:

SHEN Xuanjing, LIU Xiang, CHEN Haipeng. Fast Computation of Threshold Based on Multi-threshold Otsu Criterion[J]. Journal of Electronics & Information Technology, 2017, 39(1): 144-149. doi: 10.11999/JEIT160248

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Fast Computation of Threshold Based on Multi-threshold Otsu Criterion

doi: 10.11999/JEIT160248

Funds:

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

Received Date: 2016-03-17
Rev Recd Date: 2016-07-22
Publish Date: 2017-01-19

Abstract

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.
- Image segmentation,
- Multi-threshold Otsu criterion,
- Threshold selection,
- Fast computation

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References(25)

References

申铉京, 龙建武, 陈海鹏, 等. 三维直方图重建和降维的Otsu阈值分割算法[J]. 电子学报, 2011, 39(5) : 1108-1114.

SHEN Xuanjing, LONG Jianwu, CHEN Haipeng, et al. Otsu thresholding algorithm based on rebuilding and dimension reduction of the 3-dimensional histogram[J]. Acta Electronica Sinica, 2011, 39(5): 1108-1114.

汪海洋, 潘德炉, 夏德深. 二维Otsu自适应阈值选取算法的快速实现[J]. 自动化学报, 2007, 33(9): 968-971. doi: 10.16383/j.aas.2007.09.004.

WANG Haiyang, PAN Delu, and XIA Deshen. A fast algorithm for two-dimensional Otsu adaptive threshold algorithm[J]. Acta Automatica Sinica, 2007, 33(9): 968-971. doi: 10.16383/j.aas.2007.09.004.

OTSU N. A threshold selection method from gray-level histograms[J]. IEEE Transactions on System, Man, and Cybemetics, 1979, 9(1): 62-66.

刘立, 焦斌亮, 刘钦龙. Otsu 多阈值算法推广实现[J]. 测绘科学, 2009, 34(6): 240-241.

LIU Li, JIAO Binliang, and LIU Qinlong. Otsu multi- threshold promotion and realization of Otsu multi-threshold segmentation method[J]. Science of Surveying and Mapping, 2009, 34(6): 240-241.

刘艳, 赵英良. Otsu多阈值快速求解算法[J]. 计算机应用, 2011, 31(12): 3363-3365. doi: 10.3724/SP.J.1087.2011.03363.

LIU Yan and ZHAO Yingliang. Quick approach of multi-threshold Otsu method for image segmentation[J]. Journal of Computer Applications, 2011, 31(12): 3363-3365. doi: 10.3724/SP.J.1087.2011.03363.

HAMMOUCHE K, DIAF M, and SIARRY P. A comparative study of various meta-heuristic techniques applied to the multilevel thresholding problem[J]. Engineering Applications of Artificial Intelligence, 2010, 23(5): 676-688. doi: 10.1016 /j.engappai.2009.09.011.

HORNG Minghuwi. A multi-level image thresholding using the honey bee mating optimization[J]. Applied Mathematics and Computation, 2010, 215(9): 3302-3310. doi: 10.1016/ j.amc.2009.10.018.

张怀柱, 向长波, 宋建中, 等. 改进的遗传算法在实时图像分割中的应用[J]. 光学精密工程, 2008, 16(2): 333-338.

ZHANG Huaizhu, XIANG Changbo, SONG Jianzhong, et al. Application of improved adaptive genetic algorithm to image segmentation in real-time[J]. Optics and Precision Engineering, 2008, 16(2): 333-338.

BHANDARI A K, KUMAR A, and SINGH G K. Modified artificial bee colony based computationally efficient multilevel thresholding for satellite image segmentation using Kapurs, Otsu and Tsallis functions[J]. Expert Systems with Applications, 2015, 42(3): 1573-1601. doi: 10.1016/j.eswa. 2014.09.049.

CHEN Zezhi , PEARS N, FREEMAN M, et al. Background subtraction in video using recursive mixture models, spatio- temporal filtering and shadow removal[C]. International Symposium on Visual Computing, Berlin, Germany, 2009: 1141-1150. doi: 10.1007/978-3-642-10520-3_109.

ARORA S, ACHARYA J, VERMA A, et al. Multi-level thresholding for image segmentation through a fast statistical recursive algorithm[J]. Pattern Recognition Letters, 2008, 29(2): 119-125. doi: 10.1016/j.patrec.2007.09.005.

范九伦, 赵凤, 张雪峰. 三维Otsu阈值分割方法的递推算法[J]. 电子学报, 2007, 35(7): 1398-1402.

FAN Jiulun, ZHAO Feng, and ZHANG Xuefeng. Recursive algorithm for three-dimensional Otsu,s thresholding segmentation method[J]. Acta Electronica Sinica, 2007, 35(7): 1398-1402.

WU Peng. Image segmentation method based on firefly algorithm and maximum entropy method[J]. Computer Engineering and Applications, 2014, 50(12): 115-119.

曲仕茹, 杨红红. 基于遗传算法参数优化的PCNN红外图像分割[J]. 强激光与粒子束, 2015, 27(5): 38-43. doi: 10.11884/ HPLPB201527.051007.

QU Shiru and YANG Honghong. Infrared image segmentation based on PCNN with genetic algorithm parameter optimization[J]. High Power Laser and Particle Beams, 2015, 27(5): 38-43. doi: 10.11884/HPLPB201527. 051007.

YUAN Xiaocui, WU Lushen, and PENG Qingjin. An improved Otsu method using the weighted object variance for defect detection[J]. Applied Surface Science, 2015, 349(15): 472-484. doi: 10.1016/j.apsusc.2015.05.033.

FAYCAL?Hamdaoui, ANIS?Sakly, and ABDELLATIF Mtibaa. Computational Intelligence Applications in Modeling and Control[M]. Germany: Springer, 2015: 343-367.

何志勇, 孙立宁, 陈立国. Otsu准则下分割阈值的快速计算[J]. 电子学报, 2013, 41(2): 267-272. doi: 10.3969/j.issn.0372- 2112.2013.02.010.

HE Zhiyong, SUN Lining, and CHEN Liguo. Fast computation of threshold based on Otsu criterion[J]. Acta Electronica Sinica, 2013, 41(2): 267-272. doi: 10.3969/j. issn.0372-2112. 2013.02.010.

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