xiaobo_tuxiangchuli

该代码实现了sift特征提取，特征点自动匹配，效率较高(The code realizes sift registration)

基于图像的条形码识别程序（识别EAN13码），只要条形码的背景部分是纯色，程序就能有相当强的鲁棒性。(Image-based bar code recognition program (recognize EAN13 code), as long as the background of the bar code is solid, the program can be quite strongly robust.)

说明：  图像融合算法，exercise1:为基于小波变化与局部能量的图像融合方法 exercise2:为基于自适应算法的图像融合算法 myfunction1~myfunction5:为性能指标评价函数(Image fusion algorithm, exercise1: wavelet-based change and the local energy method of image fusion exercise2: adaptive algorithm based on image fusion algorithm myfunction1 ~ myfunction5: performance indicators for the evaluation function)

说明：  思想：把原始图的直方图变换为均匀分布的形式，这样就增加了灰度值的动态 范围从而达到增强图像整体对比度的效果。其优点是能自动地增强整个 图像的对比度。 1、对灰度图像进行直方图的均衡化处理，达到图像增强的目的。 2、利用平均滤波和中值滤波对图像进行平滑滤波。 3、利用拉普拉斯运算对图像进行锐化滤波。(Idea: transform the histogram of the original image into the form of uniform distribution, so as to increase the dynamic gray value Range to enhance the overall contrast of the image. Its advantage is that it can automatically enhance the contrast of the whole image. 1. The gray image is processed by histogram equalization to achieve the purpose of image enhancement. 2. Average filter and median filter are used to smooth the image. 3. Using Laplace operation to sharpen the image.)

基于matlab仿真的数字水印源程序以及仿真结果，可用于毕业设计论文以及课题设计参考学习！(Matlab simulation based on digital watermarking, as well as simulation results source, can be used for graduate thesis and design subject design study!)

说明：  基于ADMM的TV正则化最小化稀疏重建算法(TV Minimization Sparse Reconstruction Algorithms Based on ADMM)

在VS2012平台上利用C++语言和opencv实现对图像的分块，并保存分块图像(Using the C++ language and OpenCV to block the image on the VS2012 platform and save the block image)

matlab嵌入水印源程序 在matlab中实现数字水印的嵌入，提取和检测(Matlab source watermark embedded in Matlab achieve digital watermark embedding and extraction and detection)

IEEE:数字水印技术引论，其中将达哦水印技术的引出、算法发展、引用等(IEEE: primer on digital watermarking technology, which will lead to Oh watermark technology, algorithm development, quoted, etc.)

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.)