mlsanityData to 7 Oct 2026

State of the Art: Image Hashing

arXiv 2108.11794 ↗First posted 26 Aug 2021cs.CVcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 1 of its 31 references that are in the map. First posted on arXiv 26 Aug 2021.

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1 of 31 references.

References · 1

  1. 2018Unsupervised Semantic Deep Hashingcited by 4

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