Computer Science ›› 2018, Vol. 45 ›› Issue (8): 247-252.doi: 10.11896/j.issn.1002-137X.2018.08.044

• Graphics, Image & Pattern Recognition • Previous Articles     Next Articles

Improved Three-dimensional Otsu Image Segmentation Algorithm

QIU Guo-qing, XIONG Geng-yun, ZHAO Wen-ming   

  1. College of Automation,Chongqing University of Posts and Telecommunications,Chongqing 400065,China
  • Received:2017-06-25 Online:2018-08-29 Published:2018-08-29

Abstract: Aiming at the problem of large calculation and long running time of the three-dimensional Otsu image segmentation algorithm,an algorithm was proposed to reduce the iterative space and search space by using one-dimensional Otsu and cuckoo search algorithm in this paper.The simulation shows that the algorithm can effectively reduce the computing time.At the same time,aiming at the problem of the error segmentation of traditional three-dimensional Otsu ima-ge algorithm due to neglecting the region of 2 to 7,a processing method was proposed.This method divides the pixels in the region of 2 to 7 into noise and non-noise points,and assigns all the pixels.The simulation result shows that the segmentation of this method is superior to that of traditional three-dimensional Otsu segmentation algorithm.

Key words: Cuckoo search algorithm, Image segmentation, Three-dimensional Otsu, Threshold

CLC Number: 

  • TP391.41
[1]WU Y Q,MENG T L,WU S H.Research progress of image thresholding methods in recent 20 years(1994-2014).Journal of Data Acquisition and Processing,2015,30(1):1-23.(in Chinese)吴一全,孟天亮,吴诗婳.图像阈值分割方法研究进展20年(1994-2014)[J].数据采集与处理,2015,30(1):1-23.
[2]ZHANG P F,LU S F,LI J Q.Multi-component segmentation of X-ray computed tomography(CT) image using multi-Otsu thresholding algorithm and scanning electron microscopy[J].Ene-rgy Exploration & Exploitation,2017,35(3):281-294.
[3]YIN P Y,WU T H.Multi-objective and multi-level imagethresholding based on dominance and diversity criteria[J].Applied Soft Computing,2017,54:62-73.
[4]OTSU N.A threshold selection method from gray-level histogram[J].IEEE Transactions on Systems,1979,9(1):62-66.
[5]JYOTIKA P,GAURAV G.Image Segmentation Using Genetic Algorithm OTSU[C]∥5th International Conference on Soft Computing for Problem Solving(SocProS).2016:473-480.
[6]LIU J Z,LI W Q.The Automatic Thresholding of Gray-Level Pictures Via Two-Dimensional OTSU Method. Acta Automatica Sinica,1993,91(1):101-105.(in Chinese)刘健庄,栗文青.灰度图象的二维Otsu自动阈值分割法[J].自动化学报,1993,19(1):101-105.
[7]JING X J,LI J F,LIU Y L.Image Segmentation Based on 3-D Maximum Between-Cluster Variance.Acta Electronica Sinica,2003,31(9):1281-1285.(in Chinese)景晓军,李剑峰,刘郁林.一种基于三维最大类间方差的图像分割算法[J].电子学报,2003,31(9):1281-1285.
[8]FAN J L,ZHAO F,ZHANG X F.Recursive Algorithm forThree-Dimensional Otsu’s Thresholding Segmentation Method.Acta Electronica Sinica,2007,35(7):1398-1402.(in Chinese)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.
[9]ZHAO F,FAN J L.Three-dimensional Otsu’s method with non local spatial gray information.Computer Engineering and Applications,2013,49(3):30-33.(in Chinese)赵凤,范九伦.融合非局部空间灰度信息的三维Otsu法[J].计算机工程与应用,2013,49(3):30-33.
[10]ZENG Y Z,WANG R M.A method for three-dimension OTSU image segmentation based on adaptive particle swarm optimization.Electronic Design Engineering,2011,19(13):173-175.(in Chinese)曾业战,王润民.基于自适应粒子群优化的三维OTSU图像分割算法[J].电子设计工程,2011,19(13):173-175.
[11]SHILPA S,SHYAM L.Multilevel thresholding based on Chao-tic Darwinian Particle Swarm Optimization for segmentation of satellite images[J].Applied Soft Computing,2017(55):503-522.
[12]HE L F,HUANG S W.Modified firefly algorithm based multilevel thresholding for color image segmentation[J].Neurocomputing,2017,240:152-174. [13]FAN J W,WANG Q P,LUO H,et al.Fast Iterative Algorithm for Segmentation Based on an Improved Three-Dimensional Otsu∥2015 National Microwave and Millimeter Wave Confe-rence.2015:5.(in Chinese)范加武,王青平,罗慧,等.基于改进的三维Otsu分割快速迭代算法∥2015年全国微波毫米波会议.2015:5.
[14]PARE S,KUMAR A,BAJAJ V.A multilevel color image segmentation technique based on cuckoo search algorithm and energy curve[J].Applied Soft Computing,2016,47(C):76-102.
[15]SUDARSHAN N,YANG X S,PRATIM S P.Color Image Segmentation By Cuckoo Search[J].Intelligent Automation and Soft Computing,2015,21(4):673-685.
[16]HE X S,LI N,YANG X S,et al.Multi-objective Cuckoo Search Algorithm.Journal of System Simulation,2015,27(4):731-737.(in Chinese)贺兴时,李娜,杨新社,等.多目标布谷鸟搜索算法[J].系统仿真学报,2015,27(4):731-737.
[17]YANG X S,DEB S.Cuckoo Search via Levy Flights[C]∥Proc.of World Congress on Nature & Biologically Inspired Computing,India.USA:IEEE Publications,2009:210-214.
[18]LIU X N,MA M.Application of Cuckoo Algorithm in Multi-threshold Image Segmeutation.Computer Engineering,2013,39(7):274-278.(in Chinese)柳新妮,马苗.布谷鸟搜索算法在多阈值图像分割中的应用[J].计算机工程,2013,39(7):274-278.
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