史露娜,兰蓉

• 1:西安邮电大学

摘要(Abstract)：

针对图像模糊集模型的构造问题,提出一种基于模糊隶属度中值的阈值分割算法。该算法选取有代表性的几种隶属度函数在给定灰度处的中值作为新的隶属度值,即提取多个隶属度值的一维统计特征,将灰度图像转化为一个模糊集合,再以α-型模糊散度为目标函数寻找最佳阈值。仿真结果显示了该算法的有效性。

关键词(KeyWords)： 阈值分割;隶属度函数;模糊集;中值;模糊散度;图像分割

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金资助项目(61571361);; 陕西省教育厅科学研究计划资助项目(16JK1709);; 陕西省科技计划资助项目(2014KJXX-72)~~

作者(Author): 史露娜,兰蓉

DOI: 10.16652/j.issn.1004-373x.2018.11.010

参考文献(References)：

• [1]聂方彦,高潮,郭永彩.基于新模糊准则与DE算法的红外人体图像分割[J].计算机应用研究,2010,27(4):1594-1597.NIE Fangyan,GAO Chao,GUO Yongcai.Infrared human image segmentation based on new fuzzy criterion and DE algorithm[J].Computer application research,2010,27(4):1594-1597.
• [2]章毓晋.图像工程[M].北京:清华大学出版社,2013:73-74.ZHANG Yujin.Image engineering[M].Beijing:Tsinghua University Press,2013:73-74.
• [3]卢易苏,陈武凡.自动分割图像新方法研究[J].计算机应用研究,2012,29(3):1127-1129.LU Yisu,CHEN Wufan.A new method for automatic segmentation of images[J].Computer application research,2012,29(3):1127-1129.
• [4]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.WU Yiquan,MENG Tianliang,WU Shihua.Research progress of image threshold segmentation method 20 years(1994-2014)[J].Data acquisition and processing,2015,30(1):1-23.
• [5]XU Caiyun.Review of research on image segmentation algorithm[J].Computer knowledge&technology,2014,10(11):2637-2639.
• [6]李娟.基于模糊理论的图像分割算法研究[D].武汉:武汉科技大学,2005.LI Juan.Research on image segmentation algorithm based on fuzzy theory[D].Wuhan:Wuhan University of Science and Technology,2005.
• [7]雷博,范九伦.二维广义模糊熵图像阈值分割法[J].光子学报,2010,39(10):1907-1914.LEI Bo,FAN Jiulun.Two-dimensional generalized fuzzy entropy image threshold segmentation method[J].Acta photonica sinica,2010,39(10):1907-1914.
• [8]许新征,丁世飞,史忠植,等.图像分割的新理论和新方法[J].电子学报,2010,38(z1):76-82.XU Xinzheng,DING Shifei,SHI Zhongzhi,et al.The new theory and method of image segmentation[J].Acta electronica sinica,2010,38(S1):76-82.
• [9]兰蓉,沈文文.基于隶属度函数平均值的阈值分割算法[J].西安邮电大学学报,2015,20(2):77-82.LAN Rong,SHEN Wenwen.Threshold segmentation algorithm based on the mean value of membership function[J].Journal of Xi’an University of Posts and Telecommunications,2015,20(2):77-82.
• [10]ZADEH L A.Fuzzy sets[J].Information and control,1965,8(3):338-353.
• [11]BEZDEK J C.Pattern recognition with fuzzy objective function algorithms[M].New York:Plenum Press,1981.
• [12]CHAIRA T,RAY A K.Segmentation using fuzzy divergence[J].Pattern recognition letters,2003,24(12):1837-1844.
• [13]BUSTINCE H,BARRENECHEA E,PAGOLA M.Image thresholding using restricted equivalence functions and maximizing the measures of similarity[J].Fuzzy sets&systems,2007,158(5):496-516.
• [14]PAGOLA M,LOPEZ-MOLINA C,FERNANDEZ J,et al.Interval type-2 fuzzy sets constructed from several membership functions:application to the fuzzy thresholding algorithm[J].IEEE transactions on fuzzy systems,2013,21(2):230-244.
• [15]兰蓉,范九伦.基于α-型相对信息的模糊散度[J].工程数学学报,2010,27(4):715-719.LAN Rong,FAN Jiulun.Fuzzy divergence based onα-type relative information[J].Journal of engineering mathematics,2010,27(4):715-719.
• [16]ZHANG H,FRITTS J E,GOLDMAN S A.Image segmentation evaluation:a survey of unsupervised methods[J].Computer vision&image understanding,2008,110(2):260-280.