Method for Combining Image Segmentation Maps on the Basis of Information Redundancy and Variation of Information Minimization

被引：4
作者：
Murashov, D. M. [1 ]
机构：
[1] Russian Acad Sci, Fed Res Ctr Computer Sci & Control, Moscow 119333, Russia
来源：
OPTOELECTRONICS INSTRUMENTATION AND DATA PROCESSING | 2022年 / 58卷 / 05期
关键词：
image segmentation; combining segmentation maps; information redundancy measure; variation of information; FUSION; MODEL;
D O I：
10.3103/S8756699022050119
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
A new two-level method based on the minimization of a dual-objective quality functional for combining image segmentation maps is proposed. The functional is formed as a weighed sum of information redundancy and variation of information values calculated from an original image and a combined segmentation map. Such a measure results in the image segmentation providing a compromise between the conditions of minimizing the quantity of selected informationally significant segments and the information dissimilarity between an original image and a resulting segmentation. The proposed method makes it possible to improve the segmentation result as compared to the method for combining segments by the criterion of an information redundancy minimum.
引用
收藏
页码：457 / 464
页数：8
相关论文
共 16 条
[1]   SLIC Superpixels Compared to State-of-the-Art Superpixel Methods [J].
Achanta, Radhakrishna ;
Shaji, Appu ;
Smith, Kevin ;
Lucchi, Aurelien ;
Fua, Pascal ;
Suesstrunk, Sabine .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2012, 34 (11) :2274-2281
[2]  
[Anonymous], 2009, 2009 WORKSHOP APPL C, DOI DOI 10.1109/WACV.2009.5403029
[3]   Contour Detection and Hierarchical Image Segmentation [J].
Arbelaez, Pablo ;
Maire, Michael ;
Fowlkes, Charless ;
Malik, Jitendra .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2011, 33 (05) :898-916
[4]  
Franek L, 2011, LECT NOTES COMPUT SC, V6495, P373, DOI 10.1007/978-3-642-19282-1_30
[5]  
Kamarainen Joni-Kristian, 2012, Machine Learning in Medical Imaging. Third International Workshop (MLMI 2012). Held in Conjunction with MICCAI 2012. Revised Selected Papers, P193, DOI 10.1007/978-3-642-35428-1_24
[6]   A Novel Fusion Approach Based on the Global Consistency Criterion to Fusing Multiple Segmentations [J].
Khelifi, Lazhar ;
Mignotte, Max .
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2017, 47 (09) :2489-2502
[7]   EFA-BMFM: A multi-criteria framework for the fusion of colour image segmentation [J].
Khelifi, Lazhar ;
Mignotte, Max .
INFORMATION FUSION, 2017, 38 :104-121
[8]  
Manduchi R., 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision, P956, DOI 10.1109/ICCV.1999.790351
[9]  
Martin D, 2001, EIGHTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOL II, PROCEEDINGS, P416, DOI 10.1109/ICCV.2001.937655
[10]  
Meila M., 2005, P 22 INT C MACH LEAR, P577, DOI [DOI 10.1145/1102351.1102424, 10.1145/1102351.1102424]
12