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《Journal of Qinghai Normal University(Natural Science Edition)》 2014-01
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Markov Image Into Shape Prior Segmentation

XIN Yue-lan;LI Wen-quan;Department of Physics,Qinghai Normal University;  
In the Markov(MRF)fusion shape prior constraint framework for image segmentation,the image segmentation problem as a maximum a posteriori(MAP)estimation of a Markov random field,in essence,is equivalent to the minimization of the Gibbs energy function.Then the shape prior information is incorporated into the Gibbs energy function by flux maximum constraint,finally using graph cut techniques for minimizing the energy function to achieve Gibbs optimal solution,the segmentation contour close to the given shape template.The experimental results show that,the efficiency of the algorithm is improved,the segmentation effect is greatly improved.
【Fund】: 国家自然科学基金资助项目(NO.60963016);; 教育部“春晖计划”合作项目(NO.Z2012100)
【CateGory Index】: TP391.41
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