Description: This code implements the well-known Chan-Vese segmentation algorithm from the paper \"Active Contours Without Edges.\"
This technique deforms an initial curve so that it separates foreground from background based on the means of the two regions. The technique is very robust to initialization and gives very nice results when there is a difference between the foreground and background means.
This code uses active contours and level sets in the implementation. It could also serve as a good framework for implementing all kinds of region-based active contour energies.
1.) Download
2.) Unzip
3.) Run >>region_seg_demo
See this site for experiments, videos, and more information on segmentation, active contours, and level sets:
[ http://www.shawnlankton.com/2007/05/active-contours/ ] Platform: |
Size: 11057 |
Author:hiyisf |
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Description: active contour算法中的经典算法：基于region的levle set算法文献-active contour algorithm classic algorithm: Based on the region s literature levle set algorithm Platform: |
Size: 444416 |
Author:杨莉 |
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Description: This code implements the well-known Chan-Vese segmentation algorithm from the paper "Active Contours Without Edges."
This technique deforms an initial curve so that it separates foreground from background based on the means of the two regions. The technique is very robust to initialization and gives very nice results when there is a difference between the foreground and background means.
This code uses active contours and level sets in the implementation. It could also serve as a good framework for implementing all kinds of region-based active contour energies.
1.) Download
2.) Unzip
3.) Run >>region_seg_demo
See this site for experiments, videos, and more information on segmentation, active contours, and level sets:
[ http://www.shawnlankton.com/2007/05/active-contours/ ] Platform: |
Size: 10240 |
Author:hiyisf |
Hits:
Description: Region based Active Contour的Matlab实现代码。很经典的方法-Region based Active Contour of Matlab code. Classic method Platform: |
Size: 15360 |
Author:李好 |
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Description: 2008年IEEE TRANSACTION关于活动轮廓的经典文献。活动轮廓在图像分割和计算机视觉中有广泛应用，本文提出局部化基于区域的活动轮廓。效果很好。-2008 IEEE TRANSACTION active contour about classic literature. Active contour in image segmentation and computer vision has extensive application of this paper, local region-based active contour. Good effect. Platform: |
Size: 1132544 |
Author:单昊 |
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Description: Region Based Active Contour Segmentation：基于活动轮廓的图像分割算法，ＭＡＴＬＡＢ代码，可用于目标提取，包括实验图片-Region Based Active Contour Segmentation: Active Contour-based image segmentation algorithm, MATLAB code, and can be used for object extraction, including the experimental image Platform: |
Size: 10240 |
Author:猪哥不亮 |
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Description: 基于区域的主动轮廓模型算法，是论文《Active Contours Without Edges》的VC算法实现-Region-based active contour model algorithm, for the paper " Active Contours Without Edges" of the VC algorithm Platform: |
Size: 8192 |
Author:胡彦冰 |
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Description: 本文主要研究基于水平集方法的活动轮廓模型图像分割，在回顾活动轮廓模
型发展的基础上，介绍了曲线演化理论及其水平集方法，证明了水平集方法可以
有稳定的数值实现方式且其处理拓扑变化的自然性，进一步引出了变分水平集方
法。
本文介绍了两种不同的几何活动轮廓模型：基于梯度信息的李纯明模型以及
基于区域信息的 Chan-Vese 模型（C-V 模型）。在分析上述两模型的优缺点上，提
出了一种改进的 C-V 模型，改进模型引入了距离约束项，同时对基于区域的外部
能量项进行了改进，使得水平集函数重新初始化寓于模型的演化之中，分割结果
对参数的依赖性减小。
-This paper mainly study image segmentation of active contour model based on
level set. After reviewing the development of the active contour model, curve evolution
and level set method are presented, then we proved that the level set method has a stable
numerical realization and can describe the topology change of the contour naturally, in
addition we introduce level set of variational method.
We introduce two different GAC models in this paper: Li Chunming model which
is based on gradient information and Chan-Vese model （C-V model） which is based
on region information. Based on the drawbacks and advantages of these two models, we
improve the C-V model by adding penalizing energy term of signed distance function,
at the same time, mending the external energy term which based on region information,
then the re-initialization of the level set can accomplish in the model evolution, and the
degree of the segmentation result depend on the parameters decline.
Platform: |
Size: 3344384 |
Author:赵昭 |
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Description: ：LBF 模型是一个著名的基于区域的活动轮廓模型。与PC（Piecewise Constant）模型不同，该模型引入了一个以高斯函数为
核函数的局部二值拟合（Local Binary Fitting，LBF）能量。因为LBF 能量能够获取图像的局部信息，所以LBF 模型解决了PC 模型
不能处理灰度不均一图像的分割问题。提出了一个改进的LBF 模型，它使用一个新的核函数代替高斯核函数-: LBF model is a well-known region-based active contour models. PC (Piecewise Constant) model, the model introduces a Gaussian function as kernel function, local binary fitting (Local Binary Fitting, LBF) energy. Because the LBF energy can obtain the image of the local information, so LBF model solves the problems of the PC model can not handle gray uneven image segmentation. Proposed a the LBF model of an improvement, it uses a new kernel function instead of the Gaussian kernel Platform: |
Size: 226304 |
Author:jim |
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Description: 计算机视觉研究的主要问题之一是运动物体的检测与跟踪, 它将图像处理、模式识别、自动控制、人
工智能和计算机等很多领域的先进技术结合在了一起, 主要应用在军事视觉制导、视频监控、医疗诊断和智能交通
等各个方面, 因此该技术已经成为一个重要的研究方向。阐述了视觉跟踪算法的研究现状和视觉跟踪算法的种类,
研究了基于区域的跟踪算法、基于模型的跟踪算法、基于特征的跟踪算法和基于主动轮廓的跟踪算法, 探讨了视觉
跟踪算法的未来研究方向。-One of the computer vision tasks is moving object detection and tracking, it combines the advanced technologies together in
many fields such as image processing, pattern recognition, automatic control, artificial intelligence, computer, etc. It is mainly used in
such aspects as military visual guidance, video monitoring, medical diagnosis, intelligent transportation, etc. Object tracking technology has
been used in many important areas, so it has become a major direction of computer vision research. The state of research in visual tracking
algorithms and the common visual tracking algorithms are discussed in this paper. The region based tracking algorithms, active contour based
tracking algorithms, feature based tracking algorithms and model based tracking algorithms are studied. The future research direction for
vision tracking algorithm is discussed. Platform: |
Size: 217088 |
Author:cp |
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Description: Region Based Active Contour Model For Intensity
Non-Uniformity Correction For Image Segmentation Platform: |
Size: 377856 |
Author:aref |
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Description: Chan-Vese模型是基于区域的几何活动轮廓模型,此模型根据灰度级的同质性进行分类，图像域包括背景区域与前景区域。-Chan-Vese geometric model is region-based active contour model, this model are classified according to the gray level of homogeneity, including the background image field area and the foreground area. Platform: |
Size: 986112 |
Author:ls |
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Description: This paper presents a novel active contour model in a variational level set formulation for simultaneous segmentation and
bias field estimation of medical images. An energy function is formulated based on improved Kullback-Leibler distance (KLD)
with likelihood ratio. According to the additive model of images with intensity inhomogeneity, we characterize the statistics of
image intensities belonging to each different object in local regions as Gaussian distributions with different means and variances.
Then, we use the Gaussian distribution with bias field as a local region descriptor in level set formulation for segmentation(This paper presents a novel active contour model in a variational level set formulation for simultaneous segmentation and
bias field estimation of medical images. An energy function is formulated based on improved Kullback-Leibler distance (KLD)
with likelihood ratio. According to the additive model of images with intensity inhomogeneity, we characterize the statistics of
image intensities belonging to each different object in local regions as Gaussian distributions with different means and variances.
Then, we use the Gaussian distribution with bias field as a local region descriptor in level set formulation for segmentation and
bias field correction of the images with inhomogeneous intensities. Therefore, image segmentation and bias field estimation are
simultaneously achieved by minimizing the level set formulation) Platform: |
Size: 2441216 |
Author:song86
|
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