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Accurate detection of out-of-control variations from digital camera devices

机译:准确检测数码相机设备失控的变化

摘要

In this paper, we propose the novel use of Statistical Process Control (SPC) as a tool for identifying anomalies in the image acquisition process of a digital camera, for the purpose of camera identification. Control charts are used to illustrate the overall level of control associated with several devices (models include Apple iPhone 3G and 3GS, Nokia N97, and Leica D-Lux4), which are in turn reviewed in accordance with the Western Electric Rules for identifying assignable causes for the observed variation. X-Moving Range and Exponentially Weighted Moving Average (EWMA) control charts are used to highlight the variation for a subset of the devices. By implementing such a statistical model, the forensic investigator is much better positioned to understand the behaviour of a particular device, and is ultimately able to identify the most unstable feature of the cameras image acquisition process, thereby establishing a suitable fingerprint for matching images to their source.
机译:在本文中,我们提出了将统计过程控制(SPC)作为一种工具,用于识别数码相机的图像采集过程中的异常,以进行相机识别。控制图用于说明与多种设备(型号包括Apple iPhone 3G和3GS,诺基亚N97和Leica D-Lux4)相关的总体控制水平,然后根据Western Electric Rules进行审查,以找出可确定的原因对于观察到的变化。 X移动范围和指数加权移动平均值(EWMA)控制图用于突出显示设备子集的变化。通过实施这样的统计模型,法医调查员可以更好地了解特定设备的行为,并最终能够识别相机图像采集过程中最不稳定的特征,从而建立合适的指纹以将图像与其匹配资源。

著录项

  • 作者

    Bateman P; Ho ATS; Woodward A;

  • 作者单位
  • 年度 2010
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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