State of the Art: Image Hashing
Computer Vision and Pattern Recognition
2021-08-27 v1
Abstract
Perceptual image hashing methods are often applied in various objectives, such as image retrieval, finding duplicate or near-duplicate images, and finding similar images from large-scale image content. The main challenge in image hashing techniques is robust feature extraction, which generates the same or similar hashes in images that are visually identical. In this article, we present a short review of the state-of-the-art traditional perceptual hashing and deep learning-based perceptual hashing methods, identifying the best approaches.
Keywords
Cite
@article{arxiv.2108.11794,
title = {State of the Art: Image Hashing},
author = {Rubel Biswas and Pablo Blanco-Medina},
journal= {arXiv preprint arXiv:2108.11794},
year = {2021}
}
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8 pages