FaceHash: Face Detection and Robust Hashing

被引：1

作者：

Steinebach, Martin ^{[1
]}

Liu, Huajian ^{[1
]}

Yannikos, York ^{[1
]}

机构：

[1] Fraunhofer SIT, Rheinstr 75, D-642955 Darmstadt, Germany

来源：

DIGITAL FORENSICS AND CYBER CRIME, (ICDF2C 2013) | 2014年 / 132卷

关键词：

Robust image hash; Face detection; Blob detection;

D O I：

10.1007/978-3-319-14289-0_8

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, we introduce a concept to counter the current weakness of robust hashing with respect to cropping. We combine face detectors and robust hashing. By doing so, the detected faces become a subarea of the overall image which always can be found as long as cropping of the image does not remove the faces. As the face detection is prone to a drift effect altering size and position of the detected face, further mechanisms are needed for robust hashing. We show how face segmentation utilizing blob algorithms can be used to implement a face-based cropping robust hash algorithm.

引用

页码：102 / 115

页数：14

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