boxFilter

检测视频中的运动目标以及阴影，并消除阴影，基于opencv，将RGB颜色空间根据一定的转换关系转换到HSV空间，最后消除阴影， 可以在vc6.0和vs2008上正常运行(Shadow detection algorithm based on HSV color space)

一个会动得圆，让学习的人更好的了解C++知识，是最基本的知识，学习工程的基本入门。(Will get round a move, so who better to learn about C++ knowledge, is the most basic knowledge, basic engineering study entry.)

矢量区域填充算法（包括汉字提取生成） 算法(Vector area filling algorithm (including the extraction of Chinese characters generated) algorithm)

VapourSynth-BM3D-master BM3D算法的原创代码，运行速度超快，参考文献《Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering》(VapourSynth-BM3D-master BM3D original algorithm code, run super-fast, Reference " Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering" )

Image Database 2.5.0 (w/ thumbnails)

：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)

该算法可以应用于计算机视觉的物体识别以及3D重构中。(The algorithm can be applied to object recognition in computer vision and 3D Reconstruction.)

针对空间发光点缩成光斑图像中心的高精度提取问题，本文提出一种亚像素提取方法。该方法简历了具有高斯能量分布的空间发光点的透视投影光斑图像灰度分部数学模型，证明了空间发光点能量中心的透视投影不变性。(Light-emitting points of space shrunk to spot high-precision center of the image extraction problem, we propose a subpixel extraction method. This method resumes a space with Gaussian energy distribution points of perspective projection spot light gray segment mathematical model to prove the energy center of the space light-emitting point perspective projection invariance.)

snake算法的c源代码,一般snake算法可以用于图像的边缘检测,是一种比较新的方法(snake algorithm c source code, the general snake algorithm can be used to image edge detection, is a relatively new approach)

矩形检测：用霍夫直线检测方法来对图像中的矩形进行检测。开发环境：vc6，需要安装OpenCV。OpenCV只是用来读取和显示图像等简单操作。(Rectangle detection: Hough line detection method using the image of the rectangle to test. Development Environment: vc6, need to install OpenCV. OpenCV is used to read and display images such as simple operation.)