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此程序为基本的图像直方图处理，图像像素的填充处理及像素的平移处理，经过调试可以直接用-This program for basic image histogram processing, image processing and pixel fill-pixel translational processing, through commissioning can be directly used
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多种基于内容的视频检索镜头分割算法matlab程序，主要是检测突变，有基于直方图的方法，基于X2直方图的方法，基于像素的方法以及基于边缘轮廓法对比！对于这一领域的研究具有很好的入门作用！也是本人毕业论文所写的！视频文件建议先分离掉声音，仅保留图像系列,文件须为mpg!-A variety of content-based video retrieval lens matlab segmentation procedures, the major mutations are detected, t
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一些常用的图像处理cpp和对应的matlab接口 是非常常用的一些代码-Quick list of the source included:
imhist_thresh.cpp: Generate histogram from data,# of bins based on unique values.
imsmarthist_thresh.cpp: equalize data based on histogram
imsmartstd_thresh.cpp: equal
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kin Pixel Likelihoods and Skin Detection
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This Matlab code was developed for skin pixel detection in general imagery.
Non-parametric histogram-based models were trained using manually annotated
skin and
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本程序计算局部窗口的累积直方图，可用于驱动水平集和纹理分割- in this test program, we calculate the cumulative histogram in a local
window centered at each pixel,this local cumulative histogram can be
used to drive the level set for image and texture segmentation.
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灰度直方图是灰度级的函数，描述的是图像中具有该灰度级的像素的个数。它是多种空间域处理技术的基础。直方图操作能够有效用于图像增强；提供有用的图像统计资料，其在软件中易于计算，适用于商用硬件设备。直方图均衡化是通过对原图像进行某种变换，使原图像的灰度直方图修正为均匀分布的直方图的一种方法。图像灰度 直方图均衡化使得图像的灰度分布趋向均匀，图像所占有的像素灰度间距拉开，加大了图像反差，改善了视觉效果，达到增强目的。MATLAB是数字图像处理的常用工具，应用MATLAB的各种函数能够对数字图像进行各种处
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This Matlab code was developed for skin pixel detection in general imagery.
Non-parametric histogram-based models were trained using manually annotated
skin and non-skin pixels. A total of 14,985,845 skin pixels and 304,844,751
non-skin pixels
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This Matlab code was developed for skin pixel detection in general imagery.
Non-parametric histogram-based models were trained using manually annotated
skin and non-skin pixels. A total of 14,985,845 skin pixels and 304,844,751
non-skin pixe
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0下载：
This Matlab code was developed for skin pixel detection in general imagery.
Non-parametric histogram-based models were trained using manually annotated
skin and non-skin pixels. A total of 14,985,845 skin pixels and 304,844,751
non-skin pixe
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