PCA

基于meanshift算法的目标跟踪，主要是基于opencv车辆跟踪！！！程序当中进行简单的图像分割(Based on the meanshift algorithm of image segmentation and target tracking.)

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)

snake算法的c源代码,一般snake算法可以用于图像的边缘检测,是一种比较新的方法(snake algorithm c source code, the general snake algorithm can be used to image edge detection, is a relatively new approach)

一个用VC编的混沌图像加密程序，演示了如何读写图像，如何用混沌算法加密解密。(a program for encrypting image by chaos algorithm,based on VC.)

对图像进行平滑去噪，提高图像的质量，为后期的图像处理打基础(very good)

vc编写数字图像处理的程序,其中有图像处理的各种方法的程序(Vc write a digital image processing program, including the various methods of image processing program)

：植物种类识别方法主要是根据叶片低维特征进行自动化鉴定。然而，低维特征不能全面描述叶片信息，识别准确率低，本文提 出一种基于多特征降维的植物叶片识别方法。首先通过数字图像处理技术对植物叶片彩色样本图像进行预处理，获得去除颜色、虫洞、 叶柄和背景的叶片二值图像、灰度图像和纹理图像。然后对二值图像提取几何特征和结构特征，对灰度图像提取 Hu不变矩特征、灰 度共生矩阵特征、局部二值模式特征和 Gabor 特征，对纹理图像提取分形维数，共得到 2183 维特征参数。再采用主成分分析与线性 评判分析相结合的方法对叶片多特征进行特征降维，将叶片高维特征数据降到低维空间。使用降维后的训练样本特征数据对支持向量 机分类器进行训练(plant species identification method is mainly based on blade automatic identification of low dimensional characteristics.However, can not fully describe blade low-dimensional feature information, identification accuracy is low, in this paper A kind of plant leaves recognition method based on multiple feature dimension reduction.First by digital image processing technology to the plant leaf color sample image preprocessing, obtain background color removal, wormhole, petioles, and the blades of a binary image, gray image and texture image.Then the binary image to extract the geometric characteristics and characteristics of structure and characteristics of gray image extraction Hu moment invariants, gray co-occurrence matrix feature, local binary pattern features and Gabor, to extract the fractal dimension of texture image, get 2183 d characteristic parameters.By principal component analysis and linear uation analysis method of combining the characteristics of blade more feature dimensi)

基于小波变换的使用SPIHT算法进行图像压缩，并对原有的算法进行优化(Based on wavelet transform using the SPIHT algorithm for image compression, and the original algorithm to optimize)

说明：  对图像畸变进行校正,对有些图像由于近小远大照成的畸变进行校正，采用了opencv(To correct image distortion , It s important to the machine vision)

样条函数用于图像放大；可放大任意倍数；五次样条函数的构造 (five splines function)