KL-face-recognition

说明：  NDVI最大值合成法批量计算Python代码(Python Code for Batch Computing by NDVI Maximum Composition Method)

数字散斑相关程序，能够计算2副图片的位移，简单的例子，对初学者也许有用。(Digital speckle correlation program can calculate the displacement of two images, a simple example, may be useful for beginners.)

对于二值图像进行labeling,求的对象个数，每个对象的像素数，中心点，长宽高矮值等(labeling for bianry image)

基于双JPEG压缩统计特性的图像篡改检测方法(Image tamper detection method based on the statistical characteristics of double JPEG compression)

对背景建立均值模型，背景减除进行图像分割。()

亚像素级cvFindCornerSubPix角点检测，可较为精确地对角点进行检测(The subpixel cvFindCornerSubPix corner detection)

说明：  图像处理，通过图像融合技术，可以实现将多幅来自同一场景的图像，利用其冗余信息，融合成一幅比原来任何一幅都易于为人们所理解的图像，同时可供人们进行进一步的观察和处理(Through image fusion technology, it can realize the fusion of multiple images from the same scene, and make use of its redundant information to form an image that is easier to understand than any original image)

EKF2.0 利用扩展卡尔曼滤波器实现的SLAM算法，Matlab版本，是一个模拟的程序。运行方法为先载入mat，再运行XXX_sim函数。(EKF2.0 using the extended Kalman filter SLAM algorithm, Matlab version, is a simulation program. The method of operation for the first load the mat, run XXX_sim function.)

：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)

直方图的计算与显示分析图像、物体和视频信息过程，我们常把看到的物体用直方图（histogram）表示，直方图可以用来描述各种不同的事情，如物体的色彩分布、物体边缘梯度模板，以及表示目标位置的概率分布(Calculation and analysis of the histogram display images, objects and video information process, we often see objects with the histogram (histogram) indicates, the histogram can be used to describe a variety of different things, such as the color distribution of objects, object edges gradient templates, and the probability distribution of the target position)