FBP

VC编写的位图图像处理的源代码，包括了增强、变换等内容(VC prepared bitmap images deal with the source code, including the enhanced transformation, etc.)

使用VC++编程，自动检测角点，实现图像配准，代码可用。(Automatically detect the corner points, for image registration, the code is available.)

《基于计算机视觉的普适性三维重建方法研究》源代码，实现了一种将二维图像重建成三维场景的方法。(Source code of <General Sense Three-Dimension Reconstruction Research Based on Computer Vision>, a technique which can convert 2D images into 3D sence.)

用于火焰尖角、圆形度、纹理的测量以及图像颜色、矩阵、边缘直方图的测量(For flame sharp corners, roundness, texture measurements, and image color, matrix, edge histogram measurements)

MATLAB 计算医学图像的配准，融合 基于SIFT方法的配准()

自主选择性的查看一幅图像中的部分区域的颜色直方图：允许用户在一幅图像中选择一个矩形区域，通过按住鼠标键画一个矩形，当鼠标放开是，高亮显示矩形框，同时在另一个独立的窗口中，使用画图函数画一个图表（选定区域的颜色直方图），分别用蓝，绿，红表示选中区域中每种颜色的像素数量。(Self-selective color in an image to view a partial area of ​ ​ the histogram: Allows the user to select a rectangular area in an image by holding down the mouse button to draw a rectangle when the mouse is released, the highlighted rectangle, Meanwhile in a separate window, using the drawing functions to draw a chart (selected color histogram region), respectively, with blue, green, red indicates the number of pixels in the selected area of ​ ​ each color.)

基于opencv的MHT的多目标跟踪程序(Based on the MHT multi-target tracking program)

将DICOM文件转换为BMP文件和将BMP文件转换为DICOM文件(to DICOM conversion of BMP files and BMP file will be converted to DICOM documents)

说明：  VC++ 图像处理类库CxImage源代码，CxImage是一个可以用于MFC 的C++类，可以打开，保存，显示，转换各种格式的图像文件,比如BMP, JPEG, GIF, PNG, TIFF, MNG, ICO, PCX, TGA, WMF, WBMP, JBG, J2K 等格式的文件。可以实现BMP<->JPG，PNG <>TIFF格式等等的转换。 (VC++ image processing library CxImage source code, CxImage is a can be used MFC' s C++ classes, you can open, save, display, convert various formats of image files, such as BMP, JPEG, GIF, PNG, TIFF, MNG, ICO, PCX, TGA, WMF, WBMP, JBG, J2K and other formats. Can achieve BMP &lt -&gt JPG, PNG &lt &gt TIFF format conversion, etc..)

：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)