首页> 外文会议>Conference on Nondestructive Detection and Measurement for Homeland Security Mar 4-5, 2003 San Diego, California, USA >How to detect Edgar Allan Poe's 'purloined letter' - or: Cross correlation algorithms in digitised video images for object identification, movement evaluation and deformation analysis
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How to detect Edgar Allan Poe's 'purloined letter' - or: Cross correlation algorithms in digitised video images for object identification, movement evaluation and deformation analysis

机译:如何检测埃德加·爱伦坡(Edgar Allan Poe)的“伪字母”-或:数字化视频图像中的互相关算法,用于物体识别,运动评估和变形分析

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Cross correlation analysis of digitised grey scale patterns is based on - at least - two images which are compared one to each other. Comparison is performed by means of a two-dimensional cross correlation algorithm applied to a set of local intensity submatrices taken from the pattern matrices of the reference and the comparison images in the surrounding of predefined points of interest. Established as an outstanding NDE tool for 2D and 3D deformation field analysis with a focus on micro- and nanoscale applications (microDAC and nanoDAC), the method exhibits an additional potential for far wider applications, that could be used for advancing homeland security. Cause the cross correlation algorithm in some kind seems to imitate some of the "smart" properties of human vision, this "field-of-surface-related" method can provide alternative solutions to some object and process recognition problems that are difficult to solve with more classic "object-related" image processing methods. Detecting differences between two or more images using cross correlation techniques can open new and unusual applications in identification and detection of hidden objects or objects with unknown origin, in movement or displacement field analysis and in some aspects of biometric analysis, that could be of special interest for homeland security.
机译:数字化灰度模式的互相关分析基于-至少-两个彼此比较的图像。比较是通过二维互相关算法进行的,该算法应用到一组局部强度子矩阵,这些子矩阵从参考的图案矩阵和预定义关注点周围的比较图像中获取。该方法是2D和3D变形场分析的出色NDE工具,专注于微尺度和纳米尺度的应用(microDAC和nanoDAC),它具有广阔的应用前景,可用于促进国土安全。由于某种形式的互相关算法似乎模仿了人类视觉的某些“智能”属性,因此这种“与表面区域相关”的方法可以为某些难以解决的对象和过程识别问题提供替代解决方案。更经典的“对象相关”图像处理方法。使用互相关技术检测两个或多个图像之间的差异可以打开新的和不寻常的应用,在识别和检测隐藏的物体或来源不明的物体,运动或位移场分析以及生物特征分析的某些方面,可能会引起特别关注为了国土安全。

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