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| Graph Cut Segmentation Method Based on Multiple Priori Shape |
| XIN Yuelan1,2 , WANG Xili1, ZHANG Xiaohua3, HUANG Heming2 |
| 1.School of Computer Science, Shaanxi Nomal University, Xi′an 710119.2.Department of Physics, Qinghai Normal University, Xining 810008.3.Department of Intelligent Information System, Hiroshima Institute of Technology, Japan |
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Abstract To segment multiple objects in the graph, a graph cut segmentation method for multiple priori shape constraints is proposed. The shape distance in a discrete level set framework is used to define the priori shape model ,and then this model is merged into the regional item of the graph cut framework. The priori energy function is expanded by adding multiple shape priors. The weight coefficient of shape prior item is adaptively adjusted to realize the adaptive control of shape items accounted for the proportion of the energy function. And thus, the problem of artificial selection of parameters is solved and the efficiency of segmentation is enhanced. To obtain the invariance of the method proposed in this research for shape affine transformation, the techniques combining the scale invariant feature transform and the random sample consensus are employed to align. The experimental results indicate that multiple targets in the image can be segmented by the proposed method. Moreover, the image noise pollution as well as occlusion is inhibited.
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Received: 22 May 2015
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| About author:: XIN Yuelan, born in 1972, Ph.D. candidate, associate professor. Her research interests include image processing and pattern recognition.WANG Xili(Corresponding author),born in 1969, Ph.D., professor. Her research interests include artificial intelligence, pattern recognition and image processing.ZHANG Xiaohua, born in 1963, Ph.D., associate profe-ssor. His research interests include computer graphics, image processing and machine learning.HUANG Heming, born in 1969, Ph.D., professor. His research interests include pattern recognition.) |
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[1] 陈亚军,刘 丁,梁军利,等.一种无须预指定分割区域数的自适应多阈值图像分割方法.模式识别与人工智能, 2014, 27(11): 993-1004.
(CHEN Y J , LIU D, LIANG J L, et al. An Adaptive Multi-thre-shold Image Segmentation Method without Preassigning the Number of Segmented Regions. Pattern Recognition and Artificial Intelligence, 2014, 27(11): 993-1004.)
[2] 闫 沫,水鹏朗.一种基于AOS格式的多相水平集快速分割方法.模式识别与人工智能, 2015, 28(1): 11-18.
(YAN M, SHUI P L. A Multiphase Level Set Method for Fast Segmentation Based on AOS Scheme. Pattern Recognition and Artificial Intelligence, 2015, 28(1): 11-18.)
[3] PLATERO C, TOBAR M C, SANGUINO J, et al. A New Label Fusion Method Using Graph Cuts: Application to Hippocampus Segmentation // Proc of the XIII Mediterranean Conference on Medical and Biological Engineering and Computing. Berlin, Germany: Springer, 2014, IV: 174-177.
[4] MOHCINE B, BENAYAD N. Object Detection and Segmentation Using Adaptive MeanShift Blob Tracking Algorithm and Graph Cuts Theory // CHORASR,ed. Image Processing and Communications Challenges 5. Berlin, Germany: Springer, 2014, I: 143-151.
[5] ESSA E, XIE X H, SAZONOV I, et al. Shape Prior Model for Media-Adventitia Border Segmentation in IVUS Using Graph Cut // Proc of the 2nd International MICCAI Workshop on Medical Computer Vision, Recognition Techniques and Applications in Medical Imaging. Berlin, Germany: Springer, 2013: 114-123.
[6] GROSGEORGE D, PETITJEAN C, DACHER J N, et al. Graph Cut Segmentation with a Statistical Shape Model in Cardiac MRI. Computer Vision and Image Understanding, 2013, 117(9):1027-1035.
[7] MALCOLM J, RATHI Y, TANNENBAUM A. Graph Cut Segmentation with Nonlinear Shape Priors // Proc of the IEEE International Conference on Image Processing. San Antonio, USA: IEEE, 2007, IV: 365-368.
[8] FREEDMAN D, ZHANG T. Interactive Graph Cut Based Segmentation with Shape Priors // Proc of the IEEE Computer Society Confe-rence on Computer Vision and Pattern Recognition. San Diego, USA: IEEE, 2005, I: 755-762.
[9] WANG H, ZHANG H, RAY N. Adaptive Shape Prior in Graph Cut Image Segmentation. Pattern Recognition, 2013, 46(5): 1409-1414.
[10] SLABAUGH G, UNAL G. Graph Cuts Segmentation Using an Elliptical Shape Prior // Proc of the 12th IEEE International Conference on Image Processing. Genoa,Italy: IEEE, 2005: 1222-1225.
[11] CREMERS D, SOCHEN N, SCHNRR C. A Multiphase Dynamic Labeling Model for Variational Recognition-Driven Image Segmentation. International Journal of Computer Vision, 2006, 66(1): 67-81.
[12] 潘振宽,李 华,魏伟波,等.三维图像多相分割的变分水平集方法.计算机学报, 2009, 32(12): 2464-2474.
(PAN Z K, LI H, WEI W B, et al. A Variational Level Set Me-thod of Multiphase Segmentation for 3D Images. Chinese Journal of Computers, 2009, 32(12): 2464-2474.)
[13] MALCOLM J, RATHI Y, TANNENBAUM A. Multi-object Tra-cking through Clutter Using Graph Cuts // Proc of the 11th International Conference on Computer Vision. Madison, USA: Omnipress, 2007: 1-5.
[14] VU N, MANJUNATH B S. Shape Prior Segmentation of Multiple Objects with Graph Cuts // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. Anchorage, USA: IEEE, 2008. DOI: 10.1109/CVPR.2008.4587450.
[15] BOGOVIC J A, PRINCE J L, BAZIN P L. A Multiple Object Geometric Deformable Model for Image Segmentation. Computer Vision and Image Understanding, 2013, 117(2): 145-157.
[16] BOYKOV Y Y, JOLLY M P. Interactive Graph Cuts for Optimal Boundary & Region Segmentation of Objects in N-D Images // Proc of the 8th IEEE International Conference on Computer Vision. New York, USA: IEEE, 2001, I: 105-112.
[17] MARTIN D, FOWLKES C, TAL D, et al. A Database of Human Segmented Natural Images and Its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics // Proc of the 8th IEEE International Conference on Computer Vision. New York, USA: IEEE, 2001, II: 416-423. |
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2016, Vol. 29 
