Face-deformation

该程序可以对图像进行二值化处理，提取边缘点坐标。(The program can be two-valued image processing, extraction of the edge point coordinates.)

mean shift功能演示，实现图像分割，具体请看效果(the demonstration of the mean shift algorithm)

说明：  打包的二维三维图形图像处理源代码 稀有资源(packed 2D and 3D graphics processing source of scarce resources)

我写的贝叶斯fusion的Visual C+++源码，简明易懂，提供参数说明 可直接使用。 (The Bayesian fusion the Visual C+++ of what I wrote source, easy-to-understand parameters can be used directly.)

matlab的gui设计程序,有关<信号与系统>课程的辅助教学设计(Matlab GUI design, the relevant & lt;)

VC++Digital image processing

说明：  VC bmp图像数据读取和输出代码程序,经过编译可行(compiled vc program in reading image )

遥感摄影测量专业相邻相片同名点之间的匹配，交互界面，可以人工选点(Remote Sensing Photogrammetry Professional adjacent matching interface point between the photo of the same name, you can manually choose the point)

GraphCut算法的实现，跟踪主动镜头下的目标，效果很好！(GraphCut algorithm to track the goal of the initiative under the lens, very good!)

：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)