MATLABon-wavepack

利用相位相关法实现了图像的匹配，这种方法的优点是提取速度快，方法简单，运算量少。(Using the phase correlation method to realize the image matching, the advantage of this method is the extraction method is simple, fast, less computation.)

从一个模式识别toolbox中摘取的计算zernike不变矩的源代码，结果为图像的n阶m重zernike不变矩(From a pattern recognition toolbox extracted Zernike moment invariants calculation of the source code, the results of image re-n-order m Zernike moment invariants)

：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)

全变分程序，可以用来处理一维的信号去噪问题！！！！！(total variation)

地震剖面代码,横坐标是时间，纵坐标是道数.(Seismic code, the abscissa is the time, the ordinate is the number.)

说明：  自己写的位图三态按钮还添加了按钮声音,对自己制作图形界面有很大帮助(Write your own bitmap three-state buttons to add the button sounds right to produce their own graphical interface helps a lot)

BRISK特征点提取源代码，Linux及Windows，MATLAB环境。(Linux and Windows)

在matlab平台上实现对医学图像人脑部的分割采用c语言编写(In matlab platform to realize human brain medical image segmentation using c language)

改进的水平集方法，采用C_V模型进化。为多相位(improve the level set method, C_V evolutionary model. For the multi-phase)

图片的预处理 将图片读入之后 经过灰度处理 中值滤波（多次） sobel算子运算 二值化运算 最后做细化 处理 显示并保存 细化后的图象(Pretreatment of the picture after the picture to read through the gray scale median filter processing (multiple) sobel operator Binary operator to do the final thinning operation display and save the image after thinning)