Assignment2_santosh.tar

该程序是我多年的经验总结以及代码，实现了全景目标跟踪、火焰识别、烟雾识别、起立坐下行为判断、越界闯入、徘徊、违规停车等多种智能功能一体化，粒子滤波、贝叶斯分类器、随机森林等多种在线学习机制，还有传统的camshift、meanshift、光流法、卡尔曼滤波、struck、KCF、TLD、CT、区域匹配，相位相关、轮廓跟踪等多种算法(The program is my many years of experience and code, the realization of the panorama target tracking, flame detection, smoke detection, standing up sitting judge, cross-border intrusion, wandering, illegal parking and other various intelligent functions integration, particle filter, Bayesian classifier, random forest variety of online learning mechanism, and the traditional CAMSHIFT, meanshift, optical flow method, Kalman filter, the, KCF, regional matching, phase correlation, contour tracking and other several algorithms)

NASA开源的匹配追踪分解算法，用于信号分解以及特征提取。(Matching Pursuit Decomposition is a powerful and effective iterative algorithm for signal decomposition and feature extraction. Matching Pursuit Decomposition decomposes any signal into linear combinations of its dictionary elements or atoms.)

说明：  通过编写IDL语言，实现使用IDL语言进行分区统计功能。(By writing IDL language, the function of partition statistics using IDL language is realized.)

可以采用形态学方法找出边界，比较有益的初学者的学习方法。(It s very good for a newer to learning about image processing.)

说明：  均值方差与协方差 协方差矩阵、特征值与特征向量的提取、PCA原理 人脸识别算法之EigenFace、LBPH 人脸识别应用开发案例(Mean Variance and Covariance Covariance Matrix, Extraction of Eigenvalues and Eigenvectors, PCA Principle EigenFace and LBPH of Face Recognition Algorithms Case Study of Face Recognition Application Development)

水表指针识别系统，能够从外部导入任何一个bmp图像，最好是水表图，能够对该图形操作并读出图中水表的度数 (meter target identification system from the outside into any one bmp image, preferably meter map, Graphics to be able to operate and read out the map meter reading)

基本图像处理用C++的实现。包括平移旋转翻转边缘提取canny算子等(The basic image processing with C + +.)

水平百叶窗显示图片，讲一张图像垂直分成若干份，bitblt一行一行的显示(The level of blinds show pictures, talk about an image vertically divided into several copies, bitblt display line by line)

对有噪声的图像进行图像复原，通过迭代算法实现此功能(Image restoration for noisy images, this function is implemented by an iterative algorithm)

说明：  SRM空间富模型隐写分析算法,选区高维特征，使用集成分类器进行训练(Spatial Rich Model Steganalysis Algorithms, Selection of High-Dimensional Features, Using Integrated Classifier for Training)