Novel technique for multiresolution color image segmentation

被引:9
作者
Gao, JB [1 ]
Zhang, J
Fleming, MG
机构
[1] Univ Wisconsin, Dept Elect Engn & Comp Sci, Milwaukee, WI 53201 USA
[2] Med Coll Wisconsin, Dept Dermatol, Milwaukee, WI 53209 USA
关键词
image segmentation; color image segmentation; multiresolution processing; Markov random fields; mean field theory; image analysis;
D O I
10.1117/1.1432315
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
We describe a novel technique for color image segmentation. This technique includes three components: a color space transformation, Markov random field expectation-maximization (MRF-EM) segmentation, and a multiresolution implementation termed "narrow band." The color space transformation, from RGB to LUV, contributes to a perceptually reasonable segmentation result. The MRF-EM algorithm enables unsupervised segmentation and enforces a region smoothness constraint. The narrow-band, multiresolution implementation confines fine resolution processing to a small fraction of the image, thereby achieving acceleration over traditional multiresolution schemes. Experimental results with medical and TV images demonstrate the efficacy of the proposed technique. (C) 2002 Society of Photo-Optical Instrumentation Engineers.
引用
收藏
页码:608 / 614
页数:7
相关论文
共 19 条
[1]   A MULTISCALE RANDOM-FIELD MODEL FOR BAYESIAN IMAGE SEGMENTATION [J].
BOUMAN, CA ;
SHAPIRO, M .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 1994, 3 (02) :162-177
[2]  
Chandler D., 1987, INTRO MODERN STAT ME
[3]  
Chang M. M., 1994, Journal of Electronic Imaging, V3, P404, DOI 10.1117/12.183741
[4]   Robust analysis of feature spaces: Color image segmentation [J].
Comaniciu, D ;
Meer, P .
1997 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS, 1997, :750-755
[5]   MAXIMUM LIKELIHOOD FROM INCOMPLETE DATA VIA EM ALGORITHM [J].
DEMPSTER, AP ;
LAIRD, NM ;
RUBIN, DB .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL, 1977, 39 (01) :1-38
[6]   Techniques for a structural analysis of dermatoscopic imagery [J].
Fleming, MG ;
Steger, C ;
Zhang, J ;
Gao, JB ;
Cognetta, AB ;
Pollak, I ;
Dyer, CR .
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 1998, 22 (05) :375-389
[7]   BOUNDARY DETECTION BY CONSTRAINED OPTIMIZATION [J].
GEMAN, D ;
GEMAN, S ;
GRAFFIGNE, C ;
DONG, P .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1990, 12 (07) :609-628
[8]   Unsupervised color image segmentation [J].
Hance, GA ;
Umbaugh, SE ;
Moss, RH ;
Stoecker, WV .
IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE, 1996, 15 (01) :104-111
[9]  
Johnson R.A., 1982, APPL MULTIVARIATE ST
[10]   ON THE COLOR IMAGE SEGMENTATION ALGORITHM BASED ON THE THRESHOLDING AND THE FUZZY C-MEANS TECHNIQUES [J].
LIM, YW ;
LEE, SU .
PATTERN RECOGNITION, 1990, 23 (09) :935-952