搜索资源列表
multiphase_improved
- 改进的水平集方法，采用C_V模型进化。为多相位-improve the level set method, C_V evolutionary model. For the multi-phase
C_V
- C_V模型，用于图像分割，分割效果很好，值得去学习-C_V model for image segmentation, segmentation works well, it is worth to study
C_V
- matlab实现的图像分割，基于水平集的最新的C—V模型。-matlab realize image segmentation, level set based on the latest C-V model.
C_V
- C-V 图像分割 C-V 图像分割-C-V
73462706LevelSetMethod2_dll
- C_V模型的改进算法，一种很好的图像分割模型。对于MRI图像分割效果较好。-Implicit Active Contours Driven by Local Binary Fitting Energy
c_v
- 传统水平集模型的chan_vase方法 用matlab 完成的，适合初学者借鉴-Level set model of the traditional method of chan_vase done with matlab for beginners learn
C_V
- 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) -Iris Recognition based on Active Contours
C_V
- 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 -The procedure used to achieve semi-implicit scheme variational level set image segmentation methods in the " CV" model
C_V
- 用来描述铁电存储器MFIS-FET结构的C-V（即电容-电压）关系-Used to describe the ferroelectric memory MFIS-FET structure of CV (ie capacitance- voltage) relationship
C_
- C_V水平集模型图像分割算法C_V level set model for image segmentation-C_V level set model for image segmentation
C_V
- CV水平集模型实现对图像的分割，收敛快，收敛效果优于GAC 模型。-CV levelset model to realize image segementation
C_V
- 在图像处理中，有些图像既没有明显的边缘，也缺乏明显的纹理特征，传统的分割方法及GAC模型将难以成功实现图像分割。于是提出了C-V模型，其基本思想与传统的基于区域的图像分割方法是一致的：都是根据能量最小原则。 -Image processing, some of the images is neither obvious edge, but also the lack of obvious texture features, the traditional method of segmenta
C_V
- C-V模型文件，下载打开后可直接在matlab程序上运行实现图像分割结果呈现-CV model files can be directly downloaded to open the program to run in matlab image segmentation results are presented
C_V
- 采用半隐式方案实现变分水平集图像分割方法-Active contour without edge, image segmentation
C_V
- 这是一种将一般的灰度图像转化为分片常值的图像的算法-an algorithm that partition the image into a piecewise constant one
C_V
- 几何活动轮廓模型中著名的Chan-Vese模型大matlab程序代码-Chan-vese model program
MATLAB_Program
- 图像处理的一些经典算法，包含level-set,C_V,GAC等模型的代码-Some of the classic image processing algorithms, including code level-set, C_V, GAC and other models