davidlowe_correspondence

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.)

利用matlab编程技术将灰度图像归一化到0-255范围内(Normalize the image to 0-255)

FCM和稀疏场水平集用于分割医学图像分割(FCM and sparse field level set for segmentation of medical image segmentation)

自己编写的关于2013年的文章 a variational method for multi-source remote-sensing image fusion 的程序，基本实现了相关功能。(I have written a progrma about a variational method for multi-source remote-sensing image fusion publish in 2013,and the basic functions of the problems have been solved.)

基于混沌的图像比特级加密算法（新的置乱和扩散策略）(Image bit level encryption algorithm based on Chaos (New scrambling and diffusion strategy))

medical image thresholding using modified SFLA

说明：  二维码识别，matlab代码，内附二维码，内有界面，选择输入，注意输入顺序！(Two dimensional code identification, matlab code, two-dimensional code inside, interface inside, select input, pay attention to the input sequence!)

在图像中加入某个分数值（int），然后检测这个分数，要求在图像受到攻击时能有效（100％）提取这个值(In the image by adding a Score value (int), then detection of the scores, the requirements in the image can be attacked effectively (100) extraction of this value)

改变图像灰度，增强图像中需要的信息，可利用与分割前处理(Change the image gray level, increase the information)

说明：  SIFT的MATLAB源码，由加州大学的一位博士编写。(SIFT the MATLAB source code, from the University of California, prepared by Dr. A.)