Journal of South China University of Technology (Natural Science Edition) ›› 2016, Vol. 44 ›› Issue (5): 48-57.doi: 10.3969/j.issn.1000-565X.2016.05.008

• Electronics, Communication & Automation Technology • Previous Articles     Next Articles

Fast Iterative Algorithm for Image Threshold Segmentation Based on Two-Dimensional Arimoto Gray Entropy

WU Yi-quan1,2,3,4 ZHU Li1 WU Shi-hua1   

  1. 1.College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,Jiangsu,China; 2.Jiangsu Provincial Key Laboratory of Pulp and Paper Science and Technology,Nanjing 210037,Jiangsu,China; 3.Key Laboratory of Freshwater Fisheries and Germplasm Resources Utilization of the Ministry of Agriculture,Freshwater Fisheries Research Center,Chinese Academy of Fishery Sciences,Wuxi 214081,Jiangsu,China; 4.Key Laboratory of Healthy Mariculture for the East China Sea,Ministry of Agriculture,Xiamen 361021,Fujian,China
  • Received:2015-06-11 Revised:2016-01-07 Online:2016-05-25 Published:2016-04-12
  • Contact: 吴一全(1963-)，男，博士，教授，博士生导师，主要从事图像处理与分析、目标检测与识别、智能信息处理研究． E-mail:nuaaimage@163.com
  • About author:吴一全(1963-)，男，博士，教授，博士生导师，主要从事图像处理与分析、目标检测与识别、智能信息处理研究．
  • Supported by:
    Supported by the National Natural Science Foundation of China(61573183)，the Jiangsu Provincial Key Labora- tory of Pulp and Paper Science and Technology(201313)，the Key Laboratory of Freshwater Fisheries and Germplasm Resources Uti- lization(KF201313)，the Key Laboratory of Healthy Magriculture for the East China Sea，Ministry of Agriculture(2013ESHML06) and the Priority Academic Program Development of Jiangsu Higher Education Institutions(2012)

PDF

267

Abstract: As the existing Arimoto entropy-based thresholding methods only depend on the probability information from gray histogram and need to search the whole solution space to obtain the optimal threshold with low efficiency,a fast iterative algorithm for threshold segmentation on the basis of two-dimensional Arimoto gray entropy is pro- posed.Firstly,a fast iterative algorithm for threshold selection using one-dimensional Arimoto gray entropy is pro- posed.Secondly,by taking into consideration the gray level uniformity within the object cluster and the back- ground cluster,a two-dimensional Arimoto gray entropy thresholding method on the basis of gray level-average gray level histogram is derived.Then,fast recursive formulae for intermediate variables are given.Finally,a fast ite- rative algorithm is proposed for threshold selection on the basis of two-dimensional Arimoto gray entropy,and the corresponding algorithmic formulae are derived,which helps reduce computation burden greatly.Experimental results show that the proposed algorithm is superior to five existing threshold segmentation algorithms because it runs more rapidly and is more effective in obtaining segmented images with complete objects,clear edges and rich details.

Key words: image segmentation, threshold selection, two-dimensional Arimoto gray entropy, fast iterative algorithm

CLC Number: