crazy-climber

在matlab平台上实现对医学图像人脑部的分割采用c语言编写(In matlab platform to realize human brain medical image segmentation using c language)

Reversible data hiding in images

利用小波变化实现对不同灰度图像的边缘检测(Changes implemented using wavelet different gray-scale image edge detection)

基于纹理特征的图像检索源码，用双树复小波（DT－CWT）三级分解提取图像的纹理特征(Texture-based image retrieval source code, using dual tree complex wavelet (DT-CWT) to extract texture features three levels of decomposition)

分析了纹理特征提取方法，特别是灰度共生矩阵的方法和 Gabo:小波矩的方法。并在这两种方法的基础上提出了综合灰度共生矩阵和 Gbaor小波矩的纹理特征提取方法并用于图像检索。 (matlab)

基于opencv的C语言的疲劳驾驶检测代码，肤色检测人脸(fatigue driving detecting)

说明：  360°图像序列的柱面全景拼接算法，matlab仿真程序。(360 image sequence cylindrical panoramic mosaic algorithm, matlab simulation program.)

水下图像的增强及边缘检测，效果很好，具有很好的参考作用(Underwater Image Enhancement and Edge Detection)

计算色差输出的小程序。可以输出两组颜色值之间的CIE色差(Calculation of small color difference output procedures. Can output two sets of color values of the CIE color difference between)

sift算法在cv领域的重要性不言而喻，该作者的文章引用率在cv界是number1.本篇博客只是本人把sift算法知识点整理了下，以免忘记。本文比较早的一篇博文opencv源码解析之(3)：特征点检查前言1 中有使用opencv自带的sift做了个简单的实验，而这次主要是利用Rob Hess的sift源码来做实验，其实现在的opencv版本中带的sift算法也是Rob Hess的，只是稍微包装了下。 下面来做下试验,试验sift代码采用Rob Hess的代码，opencv目前版本中的sift源码也是采用Rob Hess的。代码可以在他的主页上下载：http://blogs.oregonstate.edu/hess/code/sift/ 这里我下载的是windows版本的，并采用Qt做了个简单的界面。(sift algorithm is self-evident the importance of the cv field, the author of the article referenced in the cv sector is number1 this blog I just sift algorithm knowledge compiled under, so as not to forget. This article compares the earlier blog post opencv source code analysis (3): check the preface of the feature points 1 the opencv bring their own sift to do a simple experiment, but this time Rob Hess' s sift source to experiment. In fact, with the opencv version sift algorithm is Rob Hess, only slightly packing the next. Below to do the next test, test sift code using the code of Rob Hess, sift source opencv version of Rob Hess. The code can be downloaded on his home page: http://blogs.oregonstate.edu/hess/code/sift/ here I downloaded the windows version, and using Qt to do a simple interface.)