789CODING-FOR-mri-SEGMENTATION

PCA、LDA人脸检测，压缩包里实现了PCA、LDA、最小距离分类器，人脸检测！(PCA, LDA face detection, compression bag to achieve the PCA, LDA, minimum distance classifier, face detection!)

很好的点云滤波的文章，主要介绍了K-d树的滤波方法(Good point cloud filtering articles, Kd tree filtering method)

这是一个matlab tld算法，供大家参考(This is a matlab tld algorithm, for your reference)

【实例简介】C#利用baslerSDK实现相机采集图像  采集图像，设置参数

在图像的DCT系数上嵌入信息，图像为常见的512*512大小的灰度图（实验所用图像为LENA.BMP）。嵌入的信息为一二进制Logo图（实验所用logo图为tj-logo.bmp），该图大小为32*32，共1024个Bit。 1. 在LENA图中嵌入水印，输出嵌入后的水印图像。 2. 对水印图像解码，输出解码后得到的logo图，并统计错误率。 3. 使用不同的嵌入强度进行嵌入，观察其对作品直觉效果和解码效果的影响，绘制相应的曲线。 4. 使用加入噪声、改变对比度、JPEG压缩等攻击方法对水印作品进行攻击，查看解码的效果。 (Information embedded in the DCT coefficients of the image, the image of the common 512* 512 size gray-scale (experimental image LENA.BMP). Information embedded in a binary Logo Figure (used in the experiment logo picture shows the tj-logo.bmp), the plot size 32* 32, 1024 Bit. LENA Figure embedded watermark, the watermark image output embedded. (2) logo watermark image decoding, the output decoded Figure statistical error rate. (3) using a different embedding strength for embedding, observe the works intuitive effects and decoding results, and draw the corresponding curve. (4) by adding the noise, change the contrast, JPEG compression attack methods to attack, to see the effect of decoding the watermark works.)

利用Matlab实现的,利用Hough变换进行圆检测算法。(The use of Matlab to achieve, the use of Hough transform for circle detection algorithm.)

基于SIFT+Kmeans+LDA的图片分类器的实现源码。 博文参考：http://www.cnblogs.com/freedomshe/archive/2012/04/24/2468747.html(The pictures classifier based on SIFT, Kmeans and LDA. Blog Reference: http://www.cnblogs.com/freedomshe/archive/2012/04/24/2468747.html)

说明：  光流法处理车辆视频，读取视频，分析单帧图片，得到光流图片(The optical flow method processes the vehicle video, reads the video, analyzes the single frame picture, obtains the optical flow picture)

该算法首先通过字典学习得到含噪图像的冗余字典，然后对相似的图像块进行聚类构成块群，并通过迭代收缩和L1正则化约束，对同类的图像块在字典上进行稀疏表示，以达到降噪的目的。实验结果表明，在常规的图像处理上，本文提出的算法能较好的保留图像的结构信息，与K-SVD和BM3D等现有的流行算法相比，具有更高的峰值信噪比（PSNR）(It firstly get the redundant dictionary of a noised image by dictionary learning.Then,the image patches are gathered according to their similarities.Meanwhile,the similar patches get sparse representation showed in dictionaries by iterative shrinkage and L1 regularization constraints and eventually the image is restored and noise is removed.The experimental results indicate that the proposed algorithm can well preserve the structure information of the common image with a higher Peak Signal to Noise Ratio(PNSR),compared with state-of-the-art algorithms,such as K-SVD and BM3D)

说明：  在计算机视觉领域一种非盲去模糊的方法代码(A non-blind deblurring method code in the field of computer vision)