Image Hash Minimization for Tamper Detection
This addresses tamper detection for image security, but appears incremental as it builds on existing hash-based methods.
The paper tackles the problem of low accuracy in tamper detection for images with small tampered areas and long hash lengths, proposing a method to minimize hash length while improving performance, though no concrete numbers are provided.
Tamper detection using image hash is a very common problem of modern days. Several research and advancements have already been done to address this problem. However, most of the existing methods lack the accuracy of tamper detection when the tampered area is low, as well as requiring long image hashes. In this paper, we propose a novel method objectively to minimize the hash length while enhancing the performance at low tampered area.