首页> 外国专利> Exposing inpainting image forgery under combination attacks with hybrid large feature mining

Exposing inpainting image forgery under combination attacks with hybrid large feature mining

机译:混合大特征挖掘在组合攻击下修复修复图像伪造

摘要

Methods and systems of detecting tampering in a digital image includes using hybrid large feature mining to identify one or more regions of an image in which tampering has occurred. Detecting tampering in a digital image with hybrid large feature mining may include spatial derivative large feature mining and transform-domain large feature mining. In some embodiments, known ensemble learning techniques are employed to address high feature dimensionality. detecting inpainting forgery includes mining features of a digital image under scrutiny based on a spatial derivative, mining one or more features of the digital image in a transform-domain; and detecting inpainting forgery in the digital image under scrutiny at least in part by the features mined based on the spatial derivative and at least in part by the features mined in the transform-domain.
机译:检测数字图像中篡改的方法和系统包括使用混合大特征挖掘来识别图像中发生篡改的一个或多个区域。利用混合大特征挖掘来检测数字图像中的篡改可以包括空间导数大特征挖掘和变换域大特征挖掘。在一些实施例中,采用已知的集成学习技术来解决高特征维数。检测修复伪造包括基于空间导数在仔细检查下挖掘数字图像的特征,在变换域中挖掘数字图像的一个或多个特征;并至少部分地根据基于空间导数的特征,以及至少部分地根据变换域中的特征,检测数字图像中的修复伪造。

著录项

  • 公开/公告号US10032265B2

    专利类型

  • 公开/公告日2018-07-24

    原文格式PDF

  • 申请/专利权人 SAM HOUSTON STATE UNIVERSITY;

    申请/专利号US201615254325

  • 发明设计人 QINGZHONG LIU;

    申请日2016-09-01

  • 分类号G06K9;G06T7;G06K9/46;G06K9/52;H04N7/167;

  • 国家 US

  • 入库时间 2022-08-21 13:05:01

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