Watermarking based image authentication and tamper detection algorithm using vector quantization approach

Tiwari, Avinash; Шарма, Маниша; Tamrakar, Raunak Kumar

doi:10.1016/j.aeue.2017.05.027

Cited by 45 publications

(9 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…To improve the quality of the watermarked image and the accuracy of tampering location, Tiwari et al [13] proposed a new watermarking algorithm for image authentication based on the vector quantization method. The watermark in the algorithm includes a robust zero-level watermark and a semi-fragile watermark.…”

Section: Spatial Domainmentioning

confidence: 99%

See 1 more Smart Citation

Review on Semi-Fragile Watermarking Algorithms for Content Authentication of Digital Images

Wang

Zhou

2017

Future Internet

View full text Add to dashboard Cite

With the popularity of network and the continuous development of multimedia technology, saving of network bandwidth and copyright protection of multimedia content have gradually attracted people's attention. The fragile watermark for integrity authentication of image data and protection of copyright has become a hotspot. In the storage and transmission process, image data must be compressed to save network bandwidth. As a result, semi-fragile watermarking techniques, which can be used to distinguish common image processing operations from malicious tampering, are emerging. In this paper, semi-fragile watermarking algorithms for image authentication are surveyed. The basic principles and characteristics about semi-fragile watermarking algorithms are introduced, and several kinds of attack behaviors are also included. Aiming at several typical image-authentication algorithms, advantages and disadvantages are analyzed, and evaluation indexes of various algorithms are compared. Finally, we analyze the key points and difficulties in the study on semi-fragile watermarking algorithms, and the direction about future development is prospected.

show abstract

Section: Spatial Domainmentioning

confidence: 99%

“…For semi-fragile watermarking algorithms in spatial domains, the pixels of digital images are processed directly to achieve the purpose of embedding watermarking information [10][11][12][13][14]. For example, some algorithms embed the watermarking information into the least significant bit (LSB) in the image pixels directly [11,12].…”

Section: Spatial Domainmentioning

confidence: 99%

Review on Semi-Fragile Watermarking Algorithms for Content Authentication of Digital Images

Wang

Zhou

2017

Future Internet

View full text Add to dashboard Cite

show abstract

“…Most of the methods differentiate in two major watermark components: authentication/check bits and recovery bits. For tamper recovery, the watermark generation which is selected using the frequency domain [2,42,56] has better results than the watermark generation using spatial domains [5,14,16], i.e. average intensity of blocks.…”

Section: Comparison and Discussionmentioning

confidence: 99%

“…However, it cannot withstand mild distortions such as random noise and JPEG compression; another disadvantage is the possibility of detection errors because the blocks used are too large, so that if one sub-block is damaged then the entire block will be marked as an error. In method [56], all extracted watermark data contribute to the recovery of content, and the accuracy of the restoration coefficient depends on the amount of available watermark data. Furthermore, the paper [44] aims to show that having a known fault location, image damage can be modelled and handled as a deletion error.…”

Section: Comparison and Discussionmentioning

confidence: 99%

A recent survey of self-embedding fragile watermarking scheme for image authentication with recovery capability

Rakhmawati

Wirawan

Suwadi

2019

J Image Video Proc.

View full text Add to dashboard Cite

The rapid developments of storage technology and information exchange encourage the development of research in the field of information security. In the process of sending information, tamper and issues about data ownership may occur. The fragile watermarking is one technique that can overcome the problem, in which this technique exploits sensitivity to tamper with the inserted watermark components. Therefore, it is not tolerable to change even only one bit. Self-embedding can be defined as some important features obtained from a selected image as a watermark by modifying the pixel value of the original image. Once a picture which has been inserted with a watermark is modified by other users, it can be used for tamper detection and recovery images. Due to the importance of this fragile watermarking scheme, this paper discusses the principles and characteristics of a fragile watermarking algorithm. The main contribution of this paper survey is that it summarises the current mechanisms of selection, generation, method of watermark insertion, detection and tamper localisation and recovery procedures. Comparison of several watermarking techniques was analysed and presented in tabular form, as well as experimental evaluation of four watermarking schemes in many graphs to show the performance of the self-embedding fragile watermarking scheme.

show abstract

“…A quantização vetorial (QV) [1], [2], que pode ser vista como uma extensão da quantização escalar em um espaço multidimensional, tem sido utilizada em diversos sistemas de processamento digital de sinais, com um amplo espectro de aplicações, dentre as quais podem ser citadas: compressão de sinais médicos [3], reconhecimento de padrões [4], compressão de voz [5], compressão de imagem [6], esteganografia e marca d'água digital [7], [8].…”

Section: Introductionunclassified

Algoritmo Baseado em Fireworks e LBG para Quantização Vetorial de Imagens

Fonseca¹,

Ferreira²,

Madeiro³

2018

Anais De XXXVI Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

View full text Add to dashboard Cite

Resumo-A quantização vetorial (QV)é uma técnica de compressão com perdas. O desempenho de sistemas de compressão de sinais baseados em QV depende da qualidade dos dicionários projetados. Este trabalho apresenta uma nova técnica de projeto de dicionários baseada no algoritmo de otimização por fogos de artifício-Fireworks Algorithm (FWA).É apresentada uma avaliação comparativa da técnica proposta com o tradicional algoritmo LBG (Linde-Buzo-Gray) e outros algoritmos de projeto de dicionários, no que diz respeitoà qualidade de imagens quantizadas, avaliada por meio da relação sinal-ruído de pico. Neste trabalho apresenta-se uma alternativa para aceleração da técnica proposta, obtida por meio da incorporação de um método eficiente de busca do vizinho mais próximoà etapa de particionamento do projeto de dicionário.

show abstract

Watermarking based image authentication and tamper detection algorithm using vector quantization approach

Cited by 45 publications

References 20 publications

Review on Semi-Fragile Watermarking Algorithms for Content Authentication of Digital Images

Review on Semi-Fragile Watermarking Algorithms for Content Authentication of Digital Images

A recent survey of self-embedding fragile watermarking scheme for image authentication with recovery capability

Algoritmo Baseado em Fireworks e LBG para Quantização Vetorial de Imagens

Contact Info

Product

Resources

About