immosaic-by--sift

画椭圆和圆和直线的二值图求边缘点斜率(Draw the ellipse and the circle and the straight line of the binary image to find the edge slopeDraw the ellipse and the circle and the straight line of the binary image to find the edge slope)

图像匹配，通过选定模板图像和要要匹配的图像，在要匹配的图像中用红色方框标记处匹配的区域。(Image matching, through the selected template image and want to match the image, to match the image using the red mark at the box matches the area.)

可利用哈夫变换法在变换域提取直线，利用g共线和直线相交的关系，使直线提取问题转化为计数问题()

对一个图像进行红蓝立体画制作，使得呈现3D效果。(to make a picture viewed as 3D)

图像分割算法，包括matlab代码，说明文档和运行结果截图(Image segmentation algorithms, including the matlab code, documentation and operating results screenshot)

一种基于CDD的图像修复算法，效果还不错，做图像修复的可以好好看看，还有论文哦 (Based CDD image restoration algorithm, the results were pretty good, do image restoration can be a good look, there are papers Oh)

通过PCL点云库对点云数据进行三维重建的好例子

对CANNY算子进行改进，其中详细的分析了CANNY算子的原理，已经应用改进的canny算子进行边缘检测，效果较好(CANNY operator improvements, including a detailed analysis of the principle of CANNY operator has been applied to improve the canny operator edge detection, better )

可以进行背景减除法-三帧法-高斯背景建模法运动检测( This file (the project file) contains information at the project level and is used to build a single project or subproject. Other users can share the project (.dsp) file, but they should export the makefiles locally. )

混合高斯(Mixture of Gaussian, MOG) 背景建模算法和Codebook 背景建模算法被广泛应用于监控视频的运动目标检测问题, 但混合高斯的球体模型通常假设RGB 三个分量是独立的, Codebook 的圆柱体模型假设背景像素值在圆柱体内均匀分布且背景亮度值变化方向指向坐标原点, 这些假设使得模型对背景的描述能力下降. 本文提出了一种椭球体背景模型, 该模型克服了混合高斯球体模型和Codebook 圆柱体模型假设的局限性, 同时利用主成分分析(Principal components analysis, PCA) 方法来刻画椭球体背景模型, 提出了一种基于主成分分析的Codebook 背景建模算法. 实验表明, 本文算法不仅能够更准确地描述背景像素值在RGB 空间中的分布特征, 而且具有良好的鲁棒性.(The background modeling algorithm of mixture of Gaussian (MOG) and codebook is widely used in moving object detection of surveillance video. However, the ball model of MOG usually assumes that the three components of RGB are independent, while the cylinder model of codebook assumes that the value of background pixel is distributed uniformly within the cylinder and the changing direction of brightness points to the origin of the coordinate system. These assumptions reduce the descriptive capability for background modeling. Therefore, the paper proposes an ellipsoid- based background model, which overcomes the MOG and codebook0s limitations. By using principal component analysis to depict the ellipsoid background model, a novel PCA-based codebook background modeling algorithm is proposed. Experiments show that this algorithm can not only give more accurate description of the distribution of background pixels but also have a better robustness.)