
Perceptual hashing is a promising solution to image content authentication. However, conventional image hash algorithms only offer a limited authentication level for the protection of overall content. In this work, we propose an image hash algorithm with block level content protection. It extracts features from DFT coefficients of image blocks. Experiments show that the hash has strong robustness against JPEG compression, scaling, additive white Gaussian noise, and Gaussian smoothing. The hash value is compact, and highly dependent on a key. It has very efficient trade-offs between the false positive rate and the true positive rate.
Technology, Science & Technology, Computer Science, Information Systems, [INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI], Computer Science, Theory & Methods, PHASE, Computer Science, ROBUST, [INFO] Computer Science [cs], Computer Science, Software Engineering, cosic
Technology, Science & Technology, Computer Science, Information Systems, [INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI], Computer Science, Theory & Methods, PHASE, Computer Science, ROBUST, [INFO] Computer Science [cs], Computer Science, Software Engineering, cosic
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 34 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
