| 基于局部熵的融合局部和全局信息的主动轮廓模型 |
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| 作者姓名： | 王海军 柳明 张圣燕 |
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| 作者单位： | 滨州学院航空信息技术研发中心, 山东 滨州 256603 |
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| 基金项目： | 滨州学院科研基金(BZXYG1214)资助 |
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| 摘 要： | 为克服局部图像模型对初始轮廓敏感的不足,结合LGDF模型和CV模型,引入图像局部熵,提出一种融合局部信息和全局信息且可以自动调节其比例的主动轮廓模型.首先由引进图像局部熵的LGDF模型和CV模型的线性组合来构造水平集演化力,然后根据图像局部信息自动调节二者的权重.实验结果表明,对血管图像、噪声图像及SAR图像,该模型显示了轮廓初始化的鲁棒性和较强的抗噪声性能.
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| 关 键 词： | 局部熵 主动轮廓模型 LGDF 模型 图像分割 水平集 |
| 收稿时间： | 2013-01-02 |
| 修稿时间： | 2013-02-28 |
An active contour model combining local and global information based on local entropy |
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| Authors: | WANG Hai-Jun LIU Ming ZHANG Sheng-Yan |
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| Institution: | Aviation IT Research & Development Center, Binzhou University, Binzhou 256603, Shandong, China |
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| Abstract: | An active contour model, which combines LGDF model and CV model and uses the image entropy, is proposed to solve the problem of sensitivity to the initial contour of the original active contour. First the level set force is defined by a linear combination of the LGDF and CV models incorporating image entropy. Then the weights of the forces are regulated by the local image information. Experiments on blood X-images, noise images, and SAR image show that the proposed method is robust to initialization and less sensitive to noises. |
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| Keywords: | local entropy active contour local gaussian distribution fitting image segmentation level set |
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