Book ChapterDOI
Edge Based Robust and Secure Perceptual Hashing Framework
Satendra Pal Singh,Gaurav Bhatnagar +1 more
- pp 490-500
TLDR
In this paper, a novel hashing framework is proposed using edge map and image normalization, the input image is normalized using geometric moments and an edge map is then employed using the canny edge detector, the estimated binary image is divided into nonoverlapping blocks and a chaotic map is used for random block selection.Abstract:
In this paper, a novel hashing framework is proposed using edge map and image normalization. In the proposed method, the input image is normalized using geometric moments and an edge map is then employed using the canny edge detector. The estimated binary image is divided into non-overlapping blocks and a chaotic map is used for random block selection. The singular value decomposition is carried out on the selected blocks for extracting the significant features followed by generation of hash value. The simulation results support the contention that the proposed technique is secure and considerately robust against a variety of image manipulations.read more
Citations
More filters
Journal ArticleDOI
Robust image hashing for content identification through contrastive self-supervised learning
TL;DR: In this article , the authors exploit the recent advances in self-supervised learning to generate a feature representation by solving a metric learning-based pretext task that enforces the robust image hashing properties for content identification systems.
References
More filters
Journal ArticleDOI
Robust and secure image hashing
TL;DR: A novel algorithm for generating an image hash based on Fourier transform features and controlled randomization is developed and it is shown that the proposed hash function is resilient to content-preserving modifications, such as moderate geometric and filtering distortions.
Journal ArticleDOI
Perceptual Image Hashing Via Feature Points: Performance Evaluation and Tradeoffs
Vishal Monga,Brian L. Evans +1 more
TL;DR: The proposed image hashing paradigm using visually significant feature points is proposed, which withstands standard benchmark attacks, including compression, geometric distortions of scaling and small-angle rotation, and common signal-processing operations.
Journal ArticleDOI
Perceptual Image Hashing Based on Shape Contexts and Local Feature Points
Xudong Lv,Z. J. Wang +1 more
TL;DR: The proposed shape-contexts-based image hashing approach using robust local feature points yields better identification performances under geometric attacks such as rotation attacks and brightness changes, and provides comparable performances under classical distortions such as additive noise, blurring, and compression.
Journal ArticleDOI
Perceptual Image Hashing Based on Virtual Watermark Detection
Fouad Khelifi,Jianmin Jiang +1 more
TL;DR: A new robust and secure perceptual image hashing technique based on virtual watermark detection that has been shown to outperform related state-of-the art techniques recently proposed in the literature in terms of robustness with respect to image processing manipulations and geometric attacks.
Proceedings ArticleDOI
Robust perceptual image hashing using feature points
Vishal Monga,Brian L. Evans +1 more
TL;DR: This work proposes an iterative feature detector to extract significant geometry preserving feature points and applies probabilistic quantization on the derived features to enhance perceptual robustness further.
Related Papers (5)
Robust Perceptual Image Hashing using SIFT and SVD
Efficient Image Hashing with Geometric Invariant Vector Distance for Copy Detection
Shiguang Liu,Ziqing Huang +1 more