SELF-READING-SYSTEM

图像处理的IPP库使用手册，包括每个函数的使用说明，以及参数的意义。(IPP library of image processing using the manual, including instructions for each function, as well as the significance of the parameters.)

基于Visual C++的图像边缘检测工程，以Canny为例(Visual C++-based image edge detection works to Canny Case)

c++实现的sift，可以分步观看实现效果(c++ implementation of the sift, you can watch step by step to achieve results)

遗传算法与FCM算法相结合实现图像分割，分割精度较好，速度较快(A combination of genetic algorithm and FCM algorithm to achieve image segmentation, segmentation accuracy is better, faster)

图形voronoi图的自动生成算法，用vc做，是基于一般图形voronoi图的算法，结合数字图形处理里的轮廓跟踪算法，使一般图形voronoi图能够根据不同的生成元总动生成。(Graph voronoi diagram automatic generation algorithm, using vc do is based on the general graph voronoi diagram algorithm, combined with digital image processing in the contour tracking algorithm, the general graph voronoi diagram to the total depending on the generator automatically generated.)

：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)

球面坐标定位法校正鱼眼图像畸变，使用visual studio 2008 编写，需要OpenCV的支持(Spherical coordinates locating fish eye image distortion correction, prepared using visual studio 2008, requires the support of OpenCV)

基于opencv 实现毛衣的瑕疵检测 属于毕业设计 功能完整(it is perfect)

use Codeblocks MinGW in openCV

MATLAB 计算医学图像的配准，融合 基于SIFT方法的配准()