PCA

：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)

多径条件下基于加权空间平滑的阵元幅相误差校正(Multipath based on weighted spatial smoothing array element amplitude and phase error correction)

用分水岭算法对三维模型进行分割处理。可以实现对三维模型的有意义分割。(Using three-dimensional model of the watershed algorithm to be dealt with separately. Three-dimensional model can achieve meaningful partition.)

图像处理系列之边缘检测篇 涵盖内容： 1>Roberts算子 2>Prewitt算子 3>Sobel算子 4>Laplacian算子(Edge Detection)

拉普拉斯算法的实现，程序是用vc++编写的(Laplasse algorithm)

基于C++的人脸分割的设计，C／Ｃ++语言、数字信号处理，最好选修过“数字图像处理”。(Based on the C++ face segmentation design, C/C++ language, digital signal processing, the best elect digital image processing.)

This program contains some basic image processing things, such as: 256 colors to grayscale, contrast stretching, anti-color, brightness change, etc.

openCV+MFC（VS2008）canny边缘检测，能用滑动条调节参数(openCV+MFC (VS2008) canny edge detection, use the slider to adjust parameters)

Matlab time-frequency analysis supporting the source code of chapter 12, please share

说明：  图形图像出来库文件，挺好用的，直接包含进工程就可以用了 (Graphic images from the library files, good used directly included into the project can be used)