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本程序采用半隐式方案实现变分水平集图像分割方法中的“C-V”模型(Active contour without edge)-This program uses the program to achieve semi-implicit variational level set image segmentation methods " CV" model (Active contour without edge)
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图像处理中经典的C-V（无边缘活动轮廓）模型和GAR（测地线活动区域）模型！- classic CV ( active contour without edge ) model and GAR (geodesic active region) model in Image processing!
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寄语活动轮廓模型的双向气球力的膨胀或者收缩的snake模型的算法程序-Expansion algorithm based on two-way active contour models balloon force or shrink snake model
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First run add_path.m,
and then run the demos in the file Demo .
This is newest active contour code for re-initialization scheme
You can also test your own images. The tested functions are in the file TEST , you can run the GAC model and
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主要是关于医学图像处理，采用的方法是C-V模型，及半隐式轮廓活动模型，取得了较好的效果-Mainly on the medical image processing, the method uses a CV model, and semi-implicit active contour models, and achieved good results
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有详实的说明，基于C-V模型的图像分割，属于活动轮廓模型，有典型的图片例子，可以直接运行，适合研究生使用。-There are detailed instructions, CV model-based image segmentation, are active contour models, with typical picture examples can be run directly, for graduate students to use.
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:人耳识别系统中,需要根据特征提取的要求实现图像的自动归一化,并且选择合适的依据使归一化后的结果具有一定的有效性和合理性。提出了一种新的外耳长轴标记法,根据外耳长轴将人耳统一到标准的尺寸和角度 运用主动形状模型算法,实现了外耳轮廓的自动搜索,且对算法进行了改进,调整了模型的初始位置。实验证明,改进后的主动形状模型(ASM)能更快速准确地收敛,且归一化的方法能够合理地将人耳标准化,为后续的特征识别提供了保障。-In the ear recognition system, it is require
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利用传统的主动轮廓提取模型，提取单个物体的轮廓，用了opencv图像处理库，通过此算法，对编程有了更深的理解。-Using traditional active contour extraction model, extracting the outline of a single body, with opencv image processing library, through this algorithm, a deeper understanding of programming.
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