zhiping

Shap Context based Shape recognition

说明：  对影像进行SavitzkyGolay平滑，去除噪点(To smooth the image and remove the noise)

目标跟踪源码，MATLAB编写的！里面包含三个子函数！(target tracking source, MATLAB! Functions of which contains three!)

利用Retinex中心环绕算法进行阴影去除，飞常详细并含有程序对应的PPT(Centers around the use of Retinex algorithm to remove the shadow, flying often detailed and contain procedures for the corresponding PPT)

平稳小波变换的matlab程序 还包括去噪 什么的应用(Stationary wavelet transform denoising matlab program also includes the application of what)

：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)

matlab使用regionprops求面积，找到连通域(Matlab uses regionprops to calculate area and find connected region)

说明：  在计算机视觉领域一种非盲去模糊的方法代码(A non-blind deblurring method code in the field of computer vision)

说明：  使用LazySnapping算法对GrabCut算法进行改进(There are advanced segmentation algorithms in the literature which extends the concepts of graph cuts. Most prominent of them are Graph cuts and Lazy Snapping. Lazy napping is an interactive image cut out tool. Lazy Snapping separates coarse and fine scale processing, making object specification and detailed adjustment easy.)

基于T熵的多阈值分割,实现了灰度图像的自动转换,以及对灰度图像的二阈值和三阈值的分割算法(T entropy-based multi-threshold segmentation grayscale image automatically converted, and the threshold grayscale images and three threshold segmentation algorithm)