rotation-and-scaling

用VC++实现给定位图的镜像，使用图像处理技术(with VC plans to mirror positioning, the use of image processing technology)

经典的斑块分析算法，计算Blob的源码，算法很好。(Classical plaque analysis algorithms to calculate Blob source code, algorithms very well.)

1、参数初始化； 2、形成边界削波数据； 3、波场初始化； 4、Zmax层波场延拓到深度Zmax-1； 5、Zi+1层波场延拓到深度Zi； 6、重复5，从Iz Nz-1开始，直到Iz 1，得测线上的频率—空间域波场； 7、频率-空间域波场对频率做反傅里叶变换，得时间-空间波场； (1, parameter initialization 2, the formation of boundary clipping data 3, wave field initialization 4, Zmax layer wave field extended to the depth of Zmax-1 5, Zi+1 layer wave field extended to the depth of Zi 6, repeat 5, starting Iz Nz-1 until Iz 1, the frequency of the test line- spatial domain wave field 7, frequency space domain wave field to frequency inverse Fourier transform, time- space field )

一个计算多边形面积和周长的程序, 同时可以把多边形显示出来, 直观展现多边形形状.(A polygon area and perimeter calculation procedures, the polygons can be displayed simultaneously, intuitive show polygonal shape.)

使用大津法选定二值化阈值，并对彩色图像做二值化处理(Otsu binarization threshold is selected, and the color images do binarization processing)

运动检测 检测人体的头部位置、整体位置、滤除影子(Motion detection detect the body and head position, the overall position of the shadow filter)

基于图像处理的人脸检测系统，通过openCV软件来实现的(Image processing based face detection system, implemented by software openCV)

灰度图像图像锐化处理，拉普拉斯变换，梯度等(Grayscale image sharpening, Laplace transforms, gradients, etc.)

VC的图形处理以及简单的程序设计，简单易懂(VC graphics processing and simple program design, simple and understandable )

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.)