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Complete class-based image processing, contains all of the source code, auto image, There are cycle detection, periodic testing, MIT Artificial Intelligence Laboratory identification of the target source.

滤波器图像增强的matlab算法实现程序。本人自己给出的程序代码(gabor wavelet matlab algorithm. Program code given by the original author)

1.支持多用户 2.支持自定义背景音乐，更个性化 3.可自定义浮动图片使留言本更漂亮(1. Support multi-user 2. Support for custom background music, more personalized 3. Customizable floating picture to make this message more beautiful)

Matlab源代码 Incremental Learning for Robust Visual Tracking, International Journal of Computer Vision (IJCV), vol.77, no.1-3, pp.125-141, 2008.(Matlab source code for Incremental Learning for Robust Visual Tracking, International Journal of Computer Vision (IJCV), vol.77, no.1-3, pp.125-141, 2008.)

实现shift算法，进行精确的图像识别，可以抵抗各种旋转、平移、缩放等仿射变换的攻击(Realize shift algorithm, an accurate image recognition, you can resist all kinds of rotation, translation, scaling affine transformation attack)

上课的课程：数字图像处理，同Labwindows/CVI实现的多个小程序，分别有：多种函数曲线的生成、多种函数曲线的生成并显示极值、二值图像的边缘追踪、二值图像的形态学处理、根据直方图选择阈值、灰度变换、均值滤波、粒子图像分析、图像的边缘检测、正弦曲线生成、直方图均衡化、直方图显示、中值滤波、自动计算阈值。(Class courses: digital image processing, Labwindows/CVI realize with multiple small program, a variety of function curve respectively, the generation, multiple function curve and display the extremum, generated binary image edge tracing, binary image histogram morphology processing, according to the choice threshold, gray transformation, average filtering, particle image analysis, image edge detection, sine curve generation, histogram equalization, histogram display, median filtering, automatic computing threshold.)

视网膜血管检测的Gabor变换和机器学习，教程 本教程将演示如何Gabor变换和广义 的线性模型（GLM）可用于视网膜血管检测 图像。 ，我们将尝试检测视网膜血管从 的训练图像，首先，Gabor滤波器与图像卷积。 GLM将使用Gabor变换的图像特征确定 （独立变量）和容器的位置 为结果（因变量）。( Retinal Vessel Detection by Gabor Transform and Machine Learning, a Tutorial This tutorial will demonstrate how Gabor transforms and generalized linear model (GLM) can be used for detection of retinal vessels in images. Specifically, we will attempt to detect the retinal vessels a training image , by first, convoluting multiple Gabor filters with the image. A GLM will be determined using the Gabor transformed images as features (the independent variables), and the locations of the vessels as the outcome (the dependent variable).)

说明：  模板匹配的一个matlab实例，程序可读性好。(template matching a Matlab example, procedures readable.)

Matlab写的SVM图像分类程序，是完整的可运行的图像分类程序，高手可以研究一下。(Matlab write SVM image classification procedure is complete working image classification procedures, experts can look at.)

用Python语言实现Poisson Image Editing（泊松图像编辑）算法(implementation of Poisson Image Editing algorithm with python.)