VCPPqiangda-tuxiang-chuli

箔条干扰的特性与雷达抗箔条技术研究，对雷达制导导引头的干扰技术进行系统研究(Characteristics of the anti-radar chaff and chaff research technology, the interference radar guidance seeker system research)

实现bmp位图的图像放大缩小，包含整个mfc的源码文件。(Achieve bmp bitmap image zoom, contains the entire mfc source files.)

有关数字图像处理的一些源码，可以实现一些处理图像的功能，但要配合数字摄像机使用(Digital image processing of the number of source, you can achieve the functions of image processing, but with the use of digital cameras)

为图像添加各种噪声，如高斯噪声、泊松噪声、椒盐噪声等。（需有openCV）(Add all kinds of noise for the image, such as Gaussian noise, Poisson noise, salt and pepper noise. (The need for openCV))

对输入视频进行处理，使用高斯背景建模的方法，得到视频前景，对于人群密度估计具有很大作用。(Processing of the input video, using a Gaussian background modeling method, to get videos prospects for population density estimation has a significant role.)

：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)

1 完成图象处理的基本功能2：二值化、边缘检测、滤波。 2 熟悉dc的部分常用功能，学习图标控制弹出框。(a complete image processing of the two basic functions : values, edge detection, filtering. 2 familiar with the dc part of the commonly used function, learning to control pop icon frame.)

opencv是图像处理中常用到的工具箱，本资料为基于此工具箱的图像处理匹配算法SURF的实现代码。(opencv is commonly used in image processing to the toolbox, the toolbox based on this information for the image processing algorithm to match the achievement of SURF code.)

稀疏矩阵的实例，讲述如何用稀疏矩阵进行实际的编程。本例是以超市购物为实际背景。(Examples of sparse matrix)

鸟瞰图校正，基于OPENCV的应用，可以把鸟瞰图校正为平面图。(Aerial view of the correction, based on the application of OPENCV, bird' s eye view can be corrected for the plan.)