Research Article
FaceHash: Face Detection and Robust Hashing
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@INPROCEEDINGS{10.1007/978-3-319-14289-0_8, author={Martin Steinebach and Huajian Liu and York Yannikos}, title={FaceHash: Face Detection and Robust Hashing}, proceedings={Digital Forensics and Cyber Crime. Fifth International Conference, ICDF2C 2013, Moscow, Russia, September 26-27, 2013, Revised Selected Papers}, proceedings_a={ICDF2C}, year={2015}, month={2}, keywords={Robust image hash Face detection Blob detection}, doi={10.1007/978-3-319-14289-0_8} }- Martin Steinebach
Huajian Liu
York Yannikos
Year: 2015
FaceHash: Face Detection and Robust Hashing
ICDF2C
Springer
DOI: 10.1007/978-3-319-14289-0_8
Abstract
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.
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