结合粗糙集与分层思想的彩色图像分割算法

doi:10.11772/j.issn.1001-9081.2015.07.2020

计算机应用 ›› 2015, Vol. 35 ›› Issue (7): 2020-2024.DOI: 10.11772/j.issn.1001-9081.2015.07.2020

结合粗糙集与分层思想的彩色图像分割算法

韩建栋, 朱婷婷, 李月香

山西大学计算机与信息技术学院, 太原 030006

收稿日期:2015-02-06 修回日期:2015-03-26 出版日期:2015-07-10 发布日期:2015-07-17
通讯作者: 韩建栋(1980-),男,山西文水人,讲师,博士,主要研究方向:计算机视觉,hanjiandong@sxu.edu.cn
作者简介:朱婷婷(1990-),女,河南开封人,硕士研究生,主要研究方向:图像处理与分析; 李月香(1958-),女,山西晋城人,教授,主要研究方向:信号分析与检测。
基金资助:
国家自然科学基金资助项目(61201453);高等学校博士学科点专项科研基金资助项目(20121401120015)。

Color image segmentation algorithm based on rough-set and hierarchical idea

HAN Jiandong, ZHU Tingting, LI Yuexiang

School of Computer and Information Technology, Shanxi University, Taiyuan Shanxi 030006, China

Received:2015-02-06 Revised:2015-03-26 Online:2015-07-10 Published:2015-07-17

摘要/Abstract

摘要：

针对彩色图像分割算法中小目标区域容易错分割以及计算复杂度高的问题,提出一种基于HSI空间的结合粗糙集理论与分层思想的彩色图像分割方法。首先,由于彩色图像HSI空间的奇异点对应于RGB空间的灰色像素点,为了消除奇异点,在RGB空间寻找"灰色区域"进行分割与标记;然后,将图像转换到HSI颜色空间,在强度I分量上,考虑到空间邻域信息以及区域分布差异,设计了变阈值渐变性同质函数对原始直方图进行加权,将加权直方图和原始直方图分别作为粗糙集的上、下近似集,构造了新的粗糙度函数进行分割;其次,针对初分割得到的每个区域,在色调H分量上采用直方图阈值化完成细分割;最后,为了避免过分割,在RGB空间上进行区域合并。相比Mushrif等提出的粗糙集分割算法(MUSHRIF M M, RAY A K. Color image segmentation: rough-set theoretic approach. Pattern Recognition Letters, 2008, 29(4): 483-493),该算法更容易分割出图像中的小目标区域,避免了因RGB三个分量的相关性造成的错误分割,算法运行速度提高了5~8倍。实验结果表明:该算法分割效果较好,具有一定的抗噪性与鲁棒性。

关键词: 彩色图像分割, 粗糙度, 同质性函数, 直方图阈值化, 区域合并

Abstract:

Aiming at false segmentation of small regions and high computational complexity in traditional color image segmentation algorithm, a hierarchical method of color image segmentation based on rough set and HIS (Hue-Saturation-Intensity) space was proposed. Firstly, for the reason that the singularities in HSI space are the achromatic pixels in RGB space, the achromatic regions of RGB space were segmented and labeled in order to remove the singularities from the original image. Secondly, the original image was converted from RGB space to HSI space. In intensity component, in view of spatial neighbor information and regional distribution difference, the original histogram was weighted by homogeneity function with changing thresholds and gradience. The weighted and original histograms were respectively used as the upper and lower approximation sets of rough set. The new roughness function was defined and applied to image segmentation. Then the different regions obtained in the previous stage were segmented according to the histogram in hue component. Finally, the homogeneous regions were merged in RGB space in order to avoid over-segmentation. Compared with the method based on rough set proposed by Mushrif etc. (MUSHRIF M M, RAY A K. Color image segmentation: rough-set theoretic approach. Pattern Recognition Letters, 2008, 29(4): 483-493), the proposed method can segment small regions easily, avoid the false segmentation caused by the correlation between RGB color components, and the executing speed is 5-8 times faster. The experimental results show the proposed method yields better segmentation, and it is efficient and robust to noise.

Key words: color image segmentation, roughness, homogeneity function, histogram thresholding, region merging

中图分类号:

TP391.413

韩建栋, 朱婷婷, 李月香. 结合粗糙集与分层思想的彩色图像分割算法[J]. 计算机应用, 2015, 35(7): 2020-2024.

HAN Jiandong, ZHU Tingting, LI Yuexiang. Color image segmentation algorithm based on rough-set and hierarchical idea[J]. Journal of Computer Applications, 2015, 35(7): 2020-2024.

参考文献

[1] LIN K, WU J, XU L. A survey on color image segmentation techniques [J]. Journal of Image and Graphics, 2005, 10(1): 1-10.(林开颜,吴军辉,徐立鸿.彩色图像分割方法综述[J].中国图象图形学报,2005,10(1):1-10.)
[2] LI Y Z, ZHANG D, XU Y. Modified local entropy-based transition region extraction and thresholding [J]. Applied Soft Computing, 2011, 11(8): 5630-5638.
[3] LI J, DANG J, WANG X, et al. Image threshold segmentation algorithm based on the biochemistry reaction rate [J]. Opto-Electronic Engineering, 2014, 41(11): 44-50.(李积英,党建武,王小鹏,等.基于生化反应速率的图像阈值分割算法[J].光电工程,2014,41(11):44-50.)
[4] MAINI R, AGGARWAL D H. Study and comparison of various image edge detection techniques [J]. International Journal of Image Processing, 2009, 3(1):1-12.
[5] NIU S, WANG S, YANG J, et al. A fast image segmentation algorithm fully based on edge information [J]. Journal of Computer-Aided Design and Computer Graphics, 2012, 24(11): 1410-1419.(钮圣城,王盛,杨晶晶,等.完全基于边缘信息的快速图像分割算法[J].计算机辅助设计与图形学学报,2012,24(11):1410-1419.)
[6] SHIH F Y, CHENG S. Automatic seeded region growing for color image segmentation [J]. Image and Vision Computing, 2005, 23(10): 877-886.
[7] LENG M, BAO S. Color image segmentation algorithm based on hue level histogram and region merging [J]. Journal of Computer Applications, 2010, 30(3): 653-656.(冷美萍,鲍苏苏.基于色调直方图和区域合并的彩色图像分割算法[J].计算机应用,2010,30(3):653-656.)
[8] PAL N R, PAL S K. A review on image segmentation techniques [J]. Pattern Recognition, 1993, 26(9): 1277-1294.
[9] CAMPADELLI P, MEDICI D, SCHETTINI R. Color image segmentation using Hopfield networks [J]. Image and Vision Computing, 1997, 15(3): 161-166.
[10] SMITH A R, BLINN J F. Blue screen matting [C]// Proceedings of the 1996 ACM SIGGRAPH Conference on Computer Graphics. New York: ACM, 1996: 259-268.
[11] MOHABEY A, RAY A K. Rough set theory based segmentation of color images [C]// Proceedings of the 19th International Conference of the North American Fuzzy Information Processing Society. Piscataway: IEEE, 2000: 338-342.
[12] CHENG H, SUN Y. A hierarchical approach to color image segmentation using homogeneity [J]. IEEE Transactions on Image Processing, 2000, 9(12): 2071-2082.
[13] ALVARADO-CERVANTES R, FELIPE-RIVERON E M. An a-daptive color similarity function for color image segmentation [C]//CIARP 2011: Proceedings of the 16th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision and Applications, LNCS 7042. Berlin: Springer, 2011: 113-124.
[14] ALVARADO-CERVANTES R, FELIPE-RIVERON E. Improved HSI color space for color image segmentation [C]// CIARP 2012: Proceedings of the 17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision and Applications, LNCS 7441. Berlin: Springer, 2012: 348-354.
[15] ZHANG C, WANG P. A new method of color image segmentation based on intensity and hue clustering [C]// ICPR 2000: Proceedings of the 15th International Conference on Pattern Recognition. Piscataway: IEEE, 2000: 613-616.
[16] JU Z, CHEN J, ZHOU J. Image segmentation based on the HSI color space and an improved mean shift [C]// IETICT 2013: Proceedings of the 2013 IET International Conference on Information and Communications Technologies. Piscataway: IEEE, 2013: 135-140.
[17] PAWLAK Z. Rough sets: Theoretical aspects of reasoning about data [M]. Norwell: Kluwer Academic Publishers, 1991: 9-16.
[18] ZHANG Y. Image engineering (Ⅲ): image understanding [M]. Beijing: Tsinghua Publishing House, 2007: 340-343.(章毓晋.图像工程(下册):图像理解[M].北京:清华大学出版社,2007:340-343.)
[19] MUSHRIF M M, RAY A K. Color image segmentation: rough-set theoretic approach [J]. Pattern Recognition Letters, 2008, 29(4): 483-493.
[20] CHENG H, JIANG X, WANG J. Color image segmentation based on homogram thresholding and region merging [J]. Pattern Recognition, 2002, 35(2): 373-393.

结合粗糙集与分层思想的彩色图像分割算法

Color image segmentation algorithm based on rough-set and hierarchical idea

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