Description: 图像分割程序，采用水平集演化的思想，实现偏微分方程中的GAC模型。Image segment source code(GAC model),which adopt the idea of level set evolving.-Image segmentation procedures, the use of level set evolution of thought, the realization of partial differential equations of the GAC model. Image segment source code (GAC model), which adopt the idea of level set evolving. Platform: |
Size: 11264 |
Author:li_ya |
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Description: 用matlab实现的医学图像分割算法，（分割最佳阈值的迭代算法）代码， 可适合初学者使用，并有图。-Using matlab to achieve the medical image segmentation algorithm, (partition optimal threshold of iterative algorithm) code which may be suitable for beginners to use, and map. Platform: |
Size: 28672 |
Author:李敏 |
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Description: 在matlab下的k-均值聚类进行图像分类分割处理-In matlab under the k-means clustering for image classification be dealt with separately Platform: |
Size: 1024 |
Author:zhang |
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Description: 此算法是Otsu提出的最大类间方差法，利用matlab进行分割图像-This algorithm is proposed by Otsu Otsu method, used to segment image in matlab Platform: |
Size: 1024 |
Author:328087418 |
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Description: 使用区域增长的算法进行区域分割。鼠标点击图像的某个区域的某个像素，并指定染色所用颜色（红绿蓝黑），程序执行的结果是用指定的颜色把某个区域显示出来。-Regional growth in the use of regional segmentation algorithm. A mouse click on the image of a pixel region, and specify the dye color used (black and red and green), implement the results of the procedure is designated an area of color to be displayed. Platform: |
Size: 1024 |
Author:cui ju |
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Description: 正则化切割图像，matlab代码实现，有样例可以直接运行。 -Regular cutting of the image, matlab code, and sample can be directly run. Platform: |
Size: 124928 |
Author:jiangkaihua |
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Description: 车牌图像分割和提取，（基于sobel算子的边缘分割）-License plate image segmentation and extraction, (based on the edge of the sobel operator split) Platform: |
Size: 23552 |
Author:wubin |
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Description: 图象分割是图象处理中的一项重要工作，虽然目前手工与自动相结合的分割方法已在实际工作中得到了广泛应用，但由于图象的多义性和复杂性，许多分割工作仍无法利用计算机来自动完成．-Image segment plays an important role in the field of image processing and currently the hybrid approach combining the manual and automatic methods is widely used in segment practice.In this paper we present an algorithm capable of locating the target object ontour of sharp tips accurately in the interactive rate Platform: |
Size: 187392 |
Author:ZT |
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Description: 图像分割是一种重要的和关键的图像分析技术，其目的是把图像分成各具特性的区域并提取出感兴趣的部分，图像分割的结果是图像特征提取和识别等图像理解的基础。对它的研究一直是图像技术研究中的热点和焦点，提出了数以千计的不同算法，虽然这些算法大都在不同程度上取得了一定的成功，但是图像分割问题还远远没有解决，这方面的研究仍然面临很多挑战。-Image segmentation is an important and critical image analysis, the purpose is to image into regions with different characteristics and extract the interesting part, the result of image segmentation is the image feature extraction and recognition based on image understanding. Study it has been a hot spot imaging technology research and focus, made thousands of different algorithms, although most of these methods to varying degrees, achieved some success, but the image segmentation problem is far from resolved, it of research still faces many challenges. Platform: |
Size: 4044800 |
Author:liujinkun |
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Description: 该演示中包含的代码演示如何氡相似的功能，可以用来提高（以及部分）在Connectome电磁图像单元格边界。
请举出下列文件如果您发现此代码有用：
Ritwik库马尔，阿梅里奥五雷纳和Hanspeter Pfister说“氡样的特点及其应用Connectomics”，接受，IEEE计算机学会研讨会在生物医学图像分析（MMBIA）2010年数学方法
http://seas.harvard.edu/〜 rkkumar
radonLikeFeaturesDemo.m：演示边缘增强用氡相似的功能，
getEdgeFeatures.m：助手为高斯函数的二阶导数滤波器
makeBarFilters.m：助手为高斯函数的二阶导数滤波器
sample.png：示例图像在此演示使用-The demo included in the code demonstrates how Radon-Like Features can be used to enhance (and segment) cell boundaries in Connectome EM images.
Please cite the following paper if you find this code useful:
Ritwik Kumar, Amelio V. Reina & Hanspeter Pfister, “Radon-Like Features and their Application to Connectomics”, accepted, IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA) 2010
http://seas.harvard.edu/~rkkumar
radonLikeFeaturesDemo.m : Demonstrates edge enhancement using Radon-Like Features
getEdgeFeatures.m : Helper function for Gaussian Second Derivative Filters
makeBarFilters.m : Helper function for Gaussian Second Derivative Filters
sample.png : Sample image for use in this demo
Platform: |
Size: 12288 |
Author:zhou |
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