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一种新颖的活动轮廓模型方法 被引量:1

A Novel Active Contour Model for Image Segmentation
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摘要 提出了一种新颖的活动轮廓模型。该模型有效地利用了测地线活动轮廓(Geodesic active contour,GAC)模型的光滑性和局部区域型CV(Local Region-based Chan-Vese Model,LRCV)模型的局部区域性。实验结果表明,该模型具有分割精度高、对初始轮廓不敏感等优点. A novel active contour method for image segmentation is given out,which utilizes the advantages of the GAC (Geodesic active contour)and the LRCV (Local Region-based Chan-Vese Model)methods.We consider the smoothing force of the GAC method and local region-based force of the LRCV method.Experimental results show that the model can effectively segment the intensity inhomogeneous images while it is robust to the initial contour.
出处 《微电子学与计算机》 CSCD 北大核心 2015年第9期161-163,共3页 Microelectronics & Computer
基金 国家自然科学基金(61402192) 江苏省自然科学基金(BK201301417) 江苏省高校自然科学研究面上项目(14KJB520006 15KJB520004) 淮安市科技发展计划(HANZ2014006) 江苏省"青蓝工程"
关键词 活动轮廓模型 水平集 图像分割 弱边界 深凹区域 active contour model level set image segmentation weak boundary deep concave shapes
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参考文献10

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二级参考文献27

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