Perceptual Image Hashing Technique for Image Authentication in WMSNs

2015 ◽  
pp. 75-103
Author(s):  
Jinse Shin ◽  
Christoph Ruland
Keyword(s):  
Image Authentication ◽  
Image Hashing

scholarly journals A Survey on Image Hashing for Image Authentication

2010 ◽  
Vol E93-D (5) ◽  
pp. 1020-1030 ◽  
Author(s):  
Yang OU ◽  
Kyung Hyune RHEE
Keyword(s):  
Image Authentication ◽  
Image Hashing

scholarly journals Adaptive CSLBP compressed image hashing

2019 ◽  
Vol 9 (4) ◽  
pp. 2982
Author(s):  
Varsha Patil ◽  
Tanuja Sarode
Keyword(s):  
Hamming Distance ◽  
Color Space ◽  
Image Authentication ◽  
Image Texture ◽  
Weight Factor ◽  
Image Hashing ◽  
Discrimination Capability ◽  
Content Change ◽  
Smooth Region ◽  
Texture Extraction

Hashing is popular technique of image authentication to identify malicious attacks and it also allows appearance changes in an image in controlled way. Image hashing is quality summarization of images. Quality summarization implies extraction and representation of powerful low level features in compact form. Proposed adaptive CSLBP compressed hashing method uses modified CSLBP (Center Symmetric Local Binary Pattern) as a basic method for texture extraction and color weight factor derived from L*a*b* color space. Image hash is generated from image texture. Color weight factors are used adaptively in average and difference forms to enhance discrimination capability of hash. For smooth region, averaging of colours used while for non-smooth region, color differencing is used. Adaptive CSLBP histogram is a compressed form of CSLBP and its quality is improved by adaptive color weight factor. Experimental results are demonstrated with two benchmarks, normalized hamming distance and ROC characteristics. Proposed method successfully differentiate between content change and content persevering modifications for color images.

scholarly journals Robust Image Hashing with Low-Rank Representation and Ring Partition

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Zhenjun Tang ◽  
Zixuan Yu ◽  
Zhixin Li ◽  
Chunqiang Yu ◽  
Xianquan Zhang
Keyword(s):  
Image Quality Assessment ◽  
Characteristic Curve ◽  
Visual Representation ◽  
Image Authentication ◽  
Saliency Map ◽  
Low Rank ◽  
Image Hashing ◽  
Copy Detection ◽  
Social Event Detection ◽  
Low Rank Representation

Image hashing has attracted much attention of the community of multimedia security in the past years. It has been successfully used in social event detection, image authentication, copy detection, image quality assessment, and so on. This paper presents a novel image hashing with low-rank representation (LRR) and ring partition. The proposed hashing finds the saliency map by the spectral residual model and exploits it to construct the visual representation of the preprocessed image. Next, the proposed hashing calculates the low-rank recovery of the visual representation by LRR and extracts the rotation-invariant hash from the low-rank recovery by ring partition. Hash similarity is finally determined by L2 norm. Extensive experiments are done to validate effectiveness of the proposed hashing. The results demonstrate that the proposed hashing can reach a good balance between robustness and discrimination and is superior to some state-of-the-art hashing algorithms in terms of the area under the receiver operating characteristic curve.

Image authentication based on robust image hashing with geometric correction

2018 ◽  
Vol 77 (19) ◽  
pp. 25409-25429 ◽  
Author(s):  
Ram Kumar Karsh ◽  
Arunav Saikia ◽  
Rabul Hussain Laskar
Keyword(s):  
Image Authentication ◽  
Image Hashing ◽  
Geometric Correction ◽  
Robust Image ◽  
Robust Image Hashing

Robust color image hashing using convolutional stacked denoising auto-encoders for image authentication

2021 ◽  
Author(s):  
Madhumita Paul ◽  
Arnab Jyoti Thakuria ◽  
Ram Kumar Karsh ◽  
Fazal Ahmed Talukdar
Keyword(s):  
Color Image ◽  
Image Authentication ◽  
Image Hashing

scholarly journals A Practical Blockchain Framework using Image Hashing for Image Authentication

2020 ◽  
Author(s):  
Manoranjan Paul ◽  
Cameron C White ◽  
Subrata Chakraborty
Keyword(s):  
New Technology ◽  
Hash Functions ◽  
Image Authentication ◽  
Image Hashing ◽  
Original Image ◽  
Multiple Image ◽  
System A ◽  
Image Hash ◽  
Authentication System ◽  
Cryptographic Hash Functions

Abstract Blockchain is a relatively new technology that can be seen as a decentralised database. Blockchain systems heavily rely on cryptographic hash functions to store their data, which makes it difficult to tamper with any data stored in the system. A topic that was researched along with blockchain is image authentication. Image authentication focuses on investigating and maintaining the integrity of images. As a blockchain system can be useful for maintaining data integrity, image authentication has the potential to be enhanced by blockchain. There are many techniques that can be used to authenticate images; the technique investigated by this work is image hashing. Image hashing is a technique used to calculate how similar two different images are. This is done by converting the images into hashes and then comparing them using a distance formula. To investigate the topic, an experiment involving a simulated blockchain was created. The blockchain acted as a database for images. This blockchain was made up of devices which contained their own unique image hashing algorithms. The blockchain was tested by creating modified copies of the images contained in the database, and then submitting them to the blockchain to see if it will return the original image. Through this experiment it was discovered that it is plausible to create an image authentication system using blockchain and image hashing. However, the design proposed by this work requires refinement, as it appears to struggle in some situations. This work shows that blockchain can be a suitable approach for authenticating images, particularly via image hashing. Other observations include that using multiple image hash algorithms at the same time can increase performance in some cases, as well as that each type of test done to the blockchain has its own unique pattern to its data.

Semi-fragile Image Authentication Using Robust Image Hashing with Localization

2009 ◽  
Author(s):  
Ammar M. Hassan ◽  
Ayoub Al-Hamadi ◽  
Bernd Michaelis ◽  
Yassin M.Y. Hasan ◽  
Mohamed A.A. Wahab
Keyword(s):  
Image Authentication ◽  
Image Hashing ◽  
Robust Image ◽  
Robust Image Hashing

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

Algorithms ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 227
Author(s):  
Ling Du ◽  
Zehong He ◽  
Yijing Wang ◽  
Xiaochao Wang ◽  
Anthony T. S. Ho
Keyword(s):  
Similarity Measures ◽  
Image Authentication ◽  
Adaptive Thresholding ◽  
Image Hashing ◽  
Memory Efficiency ◽  
Distorted Version ◽  
Benchmark Datasets ◽  
Information Set ◽  
Threshold Setting ◽  
Hashing Algorithm

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.

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