leida5.9

基于VC环境下的直线裁剪算法Cohen-Sutherland算法和Liang-Barsky算法的实现(Based on the realization of linear cutting algorithm VC environment under the Cohen-Sutherland algorithm and Liang-Barsky algorithm)

利用VTK实现图像的放大缩小，基于对话框编写的，有助于学习VTK的朋友(Using VTK to achieve the image to zoom in, based on the dialog box, prepared to help a friend learn VTK)

基于规格化Hough变换的天波超视距雷达检测前跟踪算法(Hough transform based on the normalized horizon radar detection and tracking algorithms)

说明：  对3D数据运用gpu实现八叉树，完成分割并进行渲染。(The use of 3D data on the GPU octree to achieve complete segmentation and rendering.)

这是基于VC++编写的对遥感影像分析的程序，主要是对遥感影像进行PCA变换，使得对影响分析不仅可以依托于现成软件，我们自己也可以开发(This is written in VC++ based on remote sensing image analysis program, mainly for remote sensing images PCA transform, makes impact analysis can not only rely on ready-made software, we can also develop their own)

VC中绘制坐标系、网格、常用数学函数以及辅助功能（背景色切换、坐标标题修改等）(vc draw)

小波包去噪C + +源代码，包括信号小波包分解，，最优树的选择，并重建一个,可以直接使用。 (Wavelet packet denoising C++ source code, including the signal wavelet packet decomposition, the optimal choice of the tree, and rebuild a can be used directly.)

：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)

根据指定字符分割字符串，VC++精选编程源码，很好的参考。(According to the specified character segmentation character string, VC++ select programming source code, a good reference.)

通过对二维人脸图片的特征提取进行三维人脸的重建(Through the two-dimensional face image feature extraction for three-dimensional reconstruction of human faces)