[1]尹雨山,王李进,尹义龙,等.回溯搜索优化算法辅助的多阈值图像分割[J].智能系统学报,2015,10(1):68-74.[doi:10.3969/j.issn.1673-4785.201410008]
YIN Yushan,WANG Lijin,YIN Yilong,et al.Backtracking search optimization algorithm assisted multilevel threshold for image segmentation[J].CAAI Transactions on Intelligent Systems,2015,10(1):68-74.[doi:10.3969/j.issn.1673-4785.201410008]
点击复制
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
10
期数:
2015年第1期
页码:
68-74
栏目:
学术论文—机器学习
出版日期:
2015-03-25
- Title:
-
Backtracking search optimization algorithm assisted multilevel threshold for image segmentation
- 作者:
-
尹雨山1, 王李进1,2, 尹义龙1,3, 王冰清1, 赵文婷1, 徐云龙1
-
1. 山东大学 计算机科学与技术学院, 山东 济南 250101;
2. 福建农林大学 计算机与信息学院, 福建 福州 350002;
3. 山东财经大学 计算机科学与技术学院, 山东 济南 250014
- Author(s):
-
YIN Yushan1, WANG Lijin1,2, YIN Yilong1,3, WANG Binqing1, ZHAO Wenting1, XU Yunlong1
-
1. School of Computer Science and Technology, Shandong University, Jinan 250101, China;
2. College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou 350001, China;
3. School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan 250014, China
-
- 关键词:
-
阈值法; 回溯搜索优化算法; 图像分割; Otsu; Kapur; PSNR
- Keywords:
-
threshold method; backtracking search optimization algorithm; image segmentation; Otsu; Kapur; PSNR
- 分类号:
-
TP183
- DOI:
-
10.3969/j.issn.1673-4785.201410008
- 文献标志码:
-
A
- 摘要:
-
阈值法是一种简单且有效的图像分割技术。然而阈值求解的计算量随阈值的增加而呈指数级别增长,这给多阈值图像分割带来巨大挑战。为了克服计算量过大问题,视多阈值分割模型为优化问题,分别将Otsu法和Kapur法作为目标函数,采用回溯搜索优化算法求解目标函数,实现多阈值图像分割。将提出的多阈值分割算法应用于自然图像分割,并与其他算法比较,实验结果说明基于回溯搜索优化算法的多阈值图像分割技术是可行的,而且具有较好的分割效果。
- Abstract:
-
The threshold method is a simple and effective image segmentation technique. However, the amount of calculation for solving threshold appears to be exponential amplification with the increase of threshold. This results in a huge challenge for multi-threshold image segmentation. This paper utilizes Otsu and Kapur methods as the target function in order to deal with image segmentation.In this paper, image segmentation is considered as an optimization problem whose objective function is formulated according to Otsu and Kapur methods, respectively. The backtracking search optimization algorithm is used to solve these two objective functions and to realize multi-threshold image segmentation. The proposed approach is applied to nature image segmentation and compared to other algorithms. The results showed that the multi-threshold image segmentation technique on the basis of backtracking search optimization algorithm is feasible and the segmentation effect is satisfactory.
备注/Memo
收稿日期:2014-10-8;改回日期:。
基金项目:国家自然科学基金-广东联合基金重点资助项目(U1201258).
作者简介:尹雨山,男,1990年生,硕士研究生,主要研究方向为智能信息处理及其应用;王李进,男,1977年生,副教授,主要研究方向为计算智能及其应用;尹义龙,男,1972年生,教授,博士生导师,主要研究方向为机器学习、数据挖掘、图像处理。中国人工智能学会机器学习专委会副秘书长、中国计算机学会多值逻辑与模糊逻辑专委常委、人工智能与模式识别专委会委员。主持国家自然科学基金重点项目等科研项目10余项。获国家发明专利授权6项。获2014年度山东省科技进步二等奖1项。
通讯作者:王李进.E-mail:lijinwang@fafu.edu.cn.
更新日期/Last Update:
2015-06-16