bcbjackVFWObjectTrackingSampleMean

图象的处理,Image processing Image processing(Image processing, Image processing Image processing)

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.)

说明：  用C++实现的对数变换达到图像增强效果，代码亲测可用(Logarithmic transformation realized by C++ achieves image enhancement effect, and code pro-test is available.)

数据同化框架下基于差分进化的遥感图像融合算法(Data assimilation framework based on differential evolution algorithm for remote sensing image fusion)

halcon与C#联合编程，控件功能 1,支持鼠标中键缩放和左键拖动 2,支持在图像缩放后,region,xld,roi能够复现 3,支持region,xld按照指定颜色显示,并在缩放后复现 4,支持矩形1,矩形2,圆,和直线roi的绘制 5,可以显示当前鼠标左键所在位置的图像灰度值 6,可以保存原图,或者截屏当前窗口(Halcon and C # joint programming)

MRF分割程序，C++编写，进行图像分割处理，帮助熟悉分割过程及能量最优求解(markov image segmentation, energy interation algorithm)

双目视觉经验总结，希望后面的不要犯错误。(Binocular visual experience summary, make no mistake behind.)

：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)

关于elastix医学图像配准算法库的例子程序，有助于分析elastix如何操作，是一个很好的教程(this is a example set of elastix library)

高斯混合模型的源代码。从文件中读取数据，用三个高斯混合模型进行处理(Gaussian mixture model of the source code. Read from the file data, using three Gaussian mixture model for processing)