face2_jiance

：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)

基于样本的纹理合成加速方法，MRF，基于Li-Yi Wei的论文。(Acceleration method based on texture synthesis samples, MRF, based on Li-Yi Wei of paper.)

C++ based JPEG on grayscale image DCT -> Quantization -> ZigZag -> DPCM, Runlength,-> Entropy Coding

论解读DICOM医学图像文件及其显示的VC++实施方法 是一份比较新的讨论dicon的vc实现方法的文章(read DICOM medical images and documents show that the implementation of the VC is a relatively new discussion di vc con method of the article)

说明：  双目测距bm算法，已经实现,基于vs2015+opencv3.2,测距精度很高，一米内精度一厘米误差(Binocular ranging bm algorithm, which has been implemented, is based on vs2015 + opencv3.2, which has high accuracy and one centimeter error in one meter)

采用最大方差阈值分割法，对指纹进行提取。(Using the maximum variance threshold segmentation method for fingerprint extraction.)

本程序实现位图的读写，均衡化，滤波，LBP，LTP特征提取以及基于LBP，LTP和卡方距离，最近邻分类的人脸识别，批量给图片改名等功能(The program can read and write a bitmap, equalization, filtering, LBP, LTP feature extraction and nearest neighbor classifier for face recognition based on LBP, LTP and chi-square distance, rename picture and some other functions.)

基于形状的模板匹配，用到了opencv，主体包含两部分，建模与金字塔搜索。(Based on the shape of the template matching, the use of opencv, the main body contains two parts, modeling and pyramid search.)

对测井曲线进行重构的程序，可以充分利用测井特征曲线所反应的岩性特征信息，完成多信息的融合(Log curve reconstruction procedures)

有关三维模型的泊松算法的诸多应用的实现，包括泊松重建和泊松纹理混合算法，由原作者开发，非常可靠(C++ implementation for algorithms including poisson mesh and poisson texture stitching, it is shared by author with wide utilization)