期刊文献+

一种彩色图像快速分割方法 被引量:6

Fast Approach of Color Image Segmentation
下载PDF
导出
摘要 提出一种基于HSI和FCM的彩色图像快速分割算法CISHF.首先将彩色图像从RGB色彩空间转换到HSI空间,然后联合利用S(饱和度)分量和I(亮度)分量进行粗分割,最后针对H(色调)分量进行模糊聚类.根据色调数据的特点,修正了样本数据到聚类中心的距离计算公式,给出统计有效样本权重的算法,对于有效色调值进行样本加权聚类,加快了聚类速度.实验表明,CISHF算法的运算性能大大高于标准FCM算法,获得了较好的彩色图像分割效果. In this paper, a fast approach named as CISHF is presented to segment color image. Color image was transformed from RGB space to HSI space firstly. Then rough segmentation was done by threshold value of saturation and intensity to eliminate the noise. Finally hue data was clustered by fuzzy c-means. The formula was revised to calculate the distance from sample data to the cluster center according to characteristics of hue data. The weight of effective hue value was calculated to speed up the cluster process. Experiments show that the performance of the presented algorithm is higher than standard FCM method and better segmentation effect can be obtained.
出处 《小型微型计算机系统》 CSCD 北大核心 2009年第7期1412-1416,共5页 Journal of Chinese Computer Systems
基金 国家自然科学基金项目(60673055)资助
关键词 HSI空间 模糊聚类 彩色图像分割 图像处理 HSI model FCM color image segmentation image processing
  • 相关文献

参考文献10

  • 1Cheng H D, Jiang X H, Sun Y, et al. Color image segmentation: advances and prospects [J]. Pattern Recognition, 2001, 34(12): 2259-2281.
  • 2Dunn J C. A fuzzy relative of the ISODATA process and its use in detecting compact well separated clusters[J]. Journal of Cybernetics, 1974, 3(3):32-57.
  • 3Bezdek J C. Pattern recognition with fuzzy objective function algorithms[M]. New York : Plenum Press, 1981.
  • 4Trivedi M M, Bezdek J C. Low-level segmentation of aerial images with fuzzy clustering[J]. IEEE Trans System Man Cybern, 1986, SMC-16(9): 589- 598.
  • 5Pal N R, Bezdek J C. Complexity reduction for"large image " processing[J]. IEEE Transactions on Systems, Man and Cybernetics, 2002, B32(5):598-611.
  • 6Thitimajshima P. A new modified fuzzy C-means algorithm for multispectral satellite images segmentation[C]. IEEE 2000 International Proceedings, IGARSS, 2000,4: 1684-1686.
  • 7Eschrieh S, Ke Jing-wei, Hall L O, et al. Fast accurate fuzzy clustering through data reduction[J]. IEEE Transactions on Fuzzy Systems, 2003, 11 (2): 262-270.
  • 8王璐,蔡自兴.改进的快速FCM算法[J].小型微型计算机系统,2005,26(10):1774-1777. 被引量:7
  • 9丁震,胡钟山,杨静宇,唐振民.FCM算法用于灰度图象分割的研究[J].电子学报,1997,25(5):39-43. 被引量:50
  • 10Rafael C Gonzalez, Richard E Wood. Digital image process second edition[M]. Beijing: Publishing House of Electronics Industry, 2002,125-235.

二级参考文献9

  • 1刘健庄,谢维信.高效的彩色图像塔形模糊聚类分割方法[J].西安电子科技大学学报,1993,20(1):40-46. 被引量:5
  • 2叶秀清,顾伟康,肖强.快速模糊分割算法[J].模式识别与人工智能,1996,9(1):66-70. 被引量:27
  • 3Fu K S,Pattern Recognit,1981年,14卷,1期,3页
  • 4Frank H oppner, Frank Klawonn. A new approach to fuzzy partitioning [A]. Proceedings of the Joint 9th IFSA World Congress and 20th NAFIPS International Conference[C], Vancouver, Canada: 2001. 1419-1424.
  • 5Yingkang Hu, Richard J Hathaway. On efficiency of optimization in fuzzy c-means[J]. Neural,Parallel&Scientific Computations, June 2002,10(2) :141-156.
  • 6Pal N R, Bezdek J C. Complexity reduction for “large image”processing[M]. Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, 2002.
  • 7Steven Eschrich, Jingwei Ke, Lawrence O Hall et al. Fast accurate fuzzy clustering through data reduction[J]. IEEE Transactions on Fuzzy Systems, April 2003, 11(2): 262-270.
  • 8高新波,谢维信.模糊聚类理论发展及应用的研究进展[J].科学通报,1999,44(21):2241-2251. 被引量:99
  • 9于剑.论模糊C均值算法的模糊指标[J].计算机学报,2003,26(8):968-973. 被引量:95

共引文献55

同被引文献27

引证文献6

二级引证文献20

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部