DeepPLearning_book

说明：  基于matlab车牌识别系统，主要涉及图像预处理、车牌定位、倾斜角矫正、字符切割、字符识别五个模块(License plate recognition system based on MATLAB.It mainly involves five modules: image preprocessing, license plate location, tilt angle correction, character cutting and character recognition)

说明：  《数字图像处理与机器视觉:Visual C++与Matlab实现》5 图像分割,霍夫变换,Hough变换直线检测的Matlab实现(&quot Digital image processing and machine vision: Visual C++ and Matlab to achieve&quot 5 image segmentation, Hough transform, Hough transform line detection of the Matlab implementation)

说明：  图像校正处理代码，能够运行，能够使用，并达到预期要求(Image correction processing code, able to run, use, and meet the expected requirements)

基于模板匹配的另一种人脸识别的算法，很实用，利用肤色建模来建立人脸皮肤模型(Another based on template matching algorithm for face recognition, very practical, using skin color modeling to create a human face skin model)

Visual Geometry Group项目组开发的超分辨率重建的源码，具有很好的效果。 附有详细的文档说明，可直接运行(a good super-resolution reconstruct source code developed by Visual Geometry Group, with detail description)

关于Bayes分类器的 实验数据都有 大家相互共享 很好用的软件(Bayesian classifier on the experimental data we have very good mutual sharing of software)

四边形网格扫描转化与交互式编辑 实现四边形网格交互式编辑：要求实现四边形扫描转化算法，以此为基础，实现四边形网格中所有四边形的扫描转化、颜色添充；并通过交互改变四边形顶点位置体会交互式图形系统特点。(Quadrilateral mesh scan conversion and interactive editing Quadrilateral grid interactive editing: Quadrilateral scan conversion algorithms required to achieve, on this basis, to achieve all quadrilateral quadrilateral scan conversion, color Tim charge and changing the quadrilateral vertex position by exchanging experience the interactive features of the graphics system.)

HOG特征提取，以通过测试。希望对大家能有所帮助。(HOG feature extraction, in order to pass the test. I hope we can help.)

舌像的梯度提取，然后进行分水岭分割，最后进行邻近区域合并，得到舌体图像。(tongue-image s watershed segmentation based on its gradient change.)

说明：  当前论文主要考虑的是非信号依赖的高斯噪声下的图像恢复，本程序实现了泊松噪声下的图像恢复，泊松噪声为信号依赖噪声，能够更加有效逼近实际成像系统噪声。( This is the code that was used in the papers "A Nonnnegatively Constrained Convex Programming Method for Image Reconstruction", "Total Variation-Penalized Poisson Likelihood Estimation for Ill-Posed Problems", "Tikhonov Regularized Poisson Likelihood Estimation: Theoretical Justification and a Computational Method", "An Efficient Computational Method for Total Variation with Poisson Negative-Log Likelihood", "An Analysis of Regularization by Diffusion for Ill-Posed Poisson Likelihood Estimation," "An Iterative Method for Edge-Preserving MAP Estimation when Data-Noise is Poisson", and finally, "Regularization Parameter Selection Methods for Ill-Posed Poisson Maximum Likelihood Estimation". See my publications page for more details. The main algorithm is for nonnegatively constrained, regularized Poisson likelihood estimation. At this point you can choose Tikhonov, total variation regularization, and diffusion regularization. A number of other methods are also implemented. Regularizatio)