drtoolbox

本代码程序主要是关于轮廓波变换的程序，很有条理的描述了轮廓波的实现过程。(I hoe this code can offer the help.)

基于非下采样轮廓波变换的图像融合。低频分量取平均，高频分量取绝对值最大。(nonsubsampled contourlet transform.Averaged low frequency components, high frequency components of the maximum absolute value.)

一个关于数字图像处理的PPT教程,希望对大家有所帮助(On digital image processing PPT tutorials, and they hope to help everyone)

cordic matlab simulation algorithm, Accuracy can reach 98%, Is the topic of the elementary school stage curriculum design.

非局部全变分小波域图像修复代码，实现算法WAVELET INPAINTING BY NONLOCAL TOTAL VARIATION，Xiaoqun Zhang，Tony F. Chan，Inverse Problems and Imaging，2010,4（1）(Non-local full variational wavelet domain image repair code algorithm WAVELET INPAINTING BY NONLOCAL TOTAL VARIATION Xiaoqun Zhang, Tony F. Chan, Inverse from and Imaging, 2010,4 (1))

根据RBM深度网络（Hinton，2006）进行MINST手写文字的分类器的训练，利用训练得到的权值制作了这个小程序，通过这个程序可以看出训练结果对数据集内的测试样本和训练样本都能进行很好的识别，但是对其他的手写字体识别就没有那么好了。(According to RBM depth network (Hinton, 2006) conducted MINST handwritten text classifier training, using the training to get the right value to produce this small program, this program can be seen through the results of the training data set and the training sample test samples are can be well identified, but on the other handwriting recognition is not so good.)

该源码为目标检测和跟踪算法 包括： 1. 静态背景下的背景预测法目标检测 2. 静态背景下帧间差分法目标检测 3. Mean Shift目标跟踪方法 4. 重心多目标跟踪方法 (The source code for target detection and tracking algorithm include: 1 Static background background prediction target detection 2 Static background frame difference method for target detection 3. Mean Shift tracking method 4 multi-target tracking methods focus)

Image AND Video Segmentation Current Status

图像处理-人脸识别技术：识别出图像中人物的五官形态，从而达到识别人脸的目的。(Image Processing-Face Recognition Technology)

说明：  首先对指纹图像进行预处理，包括图像的分割，增强，二值化，细化。对细化后的图像进行特征点的提取，最后通过细节特征匹配完成指纹的识别。(Firstly, the fingerprint image is preprocessed, including image segmentation, enhancement, binarization and thinning. The refined image is extracted by feature points, and the fingerprint recognition is completed by minutiae feature matching.)