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《Journal of Anhui University(Natural Science Edition)》 2013-01
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Model of the variational level set image segmentation based on visual attention features

WANG Xu-min,ZHANG Xiao-guang*(School of Science,China University of Mining and Technology,Xuzhou 221116,China)  
The robust and fusion capacity of the traditional active contour models is poor.The mathematical model of rock-bottom visual attention characteristics in image was first established based on a priori knowledge of mechanism of visual attention and theoretical framework of curve evolution,a new curve evolution energy functional model was put forward,then partial differential equations to guide the curve evolution were established according to variational level set to this energy functional.The numerical experiments showed that the model was more robust and had higher segmentation efficiency than classical active contour model.The model laid the foundation for higher level visual significant features and getting better segmentation.
【Fund】: 国家自然科学基金资助项目(11001265);; 现代焊接生产技术国家重点实验室开放课题研究基金资助项目(BG2007013)
【CateGory Index】: TP391.41
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