eusipco_2012_code

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.)

二维相位展开算法 引导相位展开方法相质量运行QualityGuidedUnwrap2D的。 运行戈尔茨坦枝剪相位展开方法GoldsteinUnwrap2D。 （3D实施质量的制导方法，可根据要求提供）(2D PHASE UNWRAPPING ALGORITHMS Run QualityGuidedUnwrap2D for the phase quality guided phase unwrapping method. Run GoldsteinUnwrap2D for Goldstein s branch cut phase unwrapping method. (3D implementation of the quality guided method available on request))

基于matlab实现干涉显微镜图像重构中的二维解包裹函数。( QualityGuidedUnwrap2D implements 2D quality guided path following phase unwrapping algorithm. Inputs: 1. Complex image in .mat double format 2. Binary mask (optional) Outputs: 1. Unwrapped phase image 2. Phase quality map This code can easily be extended for 3D phase unwrapping. Technique adapted from: D. C. Ghiglia and M. D. Pritt, Two-Dimensional Phase Unwrapping: Theory, Algorithms and Software. New York: Wiley-Interscience, 1998. Posted by Bruce Spottiswoode on 22 December 2008 2010/07/23 Modified by Carey Smith)

利用数字图像处理软件halocn来进行缺陷检测，附带有之前做工程项目的原图源代码，还有ppt和实验指导书(Halocn using digital image processing software for defect detection, comes with artwork done before the project source code, as well as ppt and experimental instructions)

图像匹配，可以实现目标图像的匹配，匹配出最相似的训练图片。(Image matching, the matching can achieve the target image, matching the most similar training images.)

林健写的Matlab在图像处理与目标识别方面的应用实验，包括染色体识别与统计、汽车牌照定位与字符识别、基于BP神经网络识别字符的简单实验。 (Lam Kin Writing at the Matlab image processing and target recognition application experiments, including chromosome identification and statistics, vehicle license positioning and character recognition, based on BP neural network easy to identify characters in the experiment.)

通过IDL，简单实现灰度变换，彩色变换等基本操作，包括图片打开保存拖拽显示(Simple implementation of gray level transformation, color transformation and other basic operations)

K均值图像分割，读入彩色图片，输出区域分割后的图片(K-means image segmentation, read full-color photographs, the output image after the region segmentation)

位图操作图形选取源码，例程程序结合易语言位图操作支持库，填充小图形的背景颜色。(Select the source bitmap graphics operations , routine program combining bitmap operations easy language support library , filled with small graphic background color.)

说明：  主成分分析算法提取特征值，使用KNN分类器，K值可调(principal component analysis)