Multi-attack Reference Hashing Generation for Image Authentication

Du, Lan; Wang, Yijing; Ho, Anthony T. S.

doi:10.1007/978-3-030-43575-2_33

Cited by 1 publication

(2 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this paper, we extend our previous work [44] and propose an image hashing algorithm framework for authentication with multi-attack reference generation and adaptive thresholding. According to the requirement of authentication application, we propose to build the prior information set based on the help of multiple virtual prior attacks, which is produced by applying virtual prior distortions and attacks on the original images.…”

Section: Introductionmentioning

confidence: 89%

“…Data dependent methods with learning [40][41][42][43] can be trained to optimally fit data distributions and specific objective functions, which produce better hashing codes to preserve the local similarity. In our previous work [44], we proposed a reference hashing method based on clustering. This algorithm makes the observation that the hashes of the original image actually not be the centroid of its cluster set.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Image Hashing Algorithm for Authentication with Multi-Attack Reference Generation and Adaptive Thresholding

Wang

et al. 2020

Algorithms

View full text Add to dashboard Cite

Image hashing-based authentication methods have been widely studied with continuous advancements owing to the speed and memory efficiency. However, reference hash generation and threshold setting, which are used for similarity measures between original images and corresponding distorted version, are important but less considered by most of existing models. In this paper, we propose an image hashing method based on multi-attack reference generation and adaptive thresholding for image authentication. We propose to build the prior information set based on the help of multiple virtual prior attacks, and present a multi-attack reference generation method based on hashing clusters. The perceptual hashing algorithm was applied to the reference/queried image to obtain the hashing codes for authentication. Furthermore, we introduce the concept of adaptive thresholding to account for variations in hashing distance. Extensive experiments on benchmark datasets have validated the effectiveness of our proposed method.

show abstract

Section: Introductionmentioning

confidence: 89%