Detecting Double JPEG Compressed Color Images With the Same Quantization Matrix in Spherical Coordinates

Wang, Jinwei; Wang, Hao; Li, Jian; Luo, Xiangyang; Shi, Yun-Qing; Jha, Sunil Kumar

doi:10.1109/tcsvt.2019.2922309

Cited by 49 publications

(23 citation statements)

References 32 publications

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“…Next, we compute the average contrast. According to (10) and (11), we denote x = H(⊗(B 0 |U)) and y = H(⊗(B 1 |U)) for any participant set U with |U| = k. From (7) and (13), we obtain…”

Section: Contrast Of the Proposed Schemementioning

confidence: 99%

“…When k or more of them are stacked together, the secret image will be recognized by the human visual system. This visual decoding method attracted much attention and was used in many applications such as visual image encoding [2][3][4], visual authentication [5,6], and steganography [7][8][9][10], as well as an important solution for secure multimedia content protection on cloud-based media hosting [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

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A Novel XOR-Based Threshold Visual Cryptography with Adjustable Pixel Expansion

et al. 2020

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A (k, n) visual cryptography (VC) scheme encodes a secret image into n shadows that are printed on transparencies distributed among a group of n participants secretly, and reveal the secret image by stacking no less than k of them. Its decryption requires no computation and attracts much attention in image security applications. The pixel expansion and contrast are two important characteristics to evaluate the visual quality of the revealed secret image for a (k, n)-VC scheme. The (k, n) XOR-based VC (XVC) schemes can greatly improve the visual quality including both pixel expansion and contrast. Previous methods require complex computation and result in high pixel expansion when they are used to construct such schemes. In this paper, we propose a pixel expansion adjustable (k, n)-XVC scheme, which allows pixel expansion to be changed among 2 k−1 − 1 different values. It can ensure each pixel being exactly recovered with the same average contrast no matter it takes any pixel expansion value. The least pixel expansion is much smaller than previous schemes. Our scheme can be easily implemented based on any conventional OR-based (k, n)-VC (OVC) scheme.

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“…Next, we compute the average contrast. According to (10) and (11), we denote x = H(⊗(B 0 |U)) and y = H(⊗(B 1 |U)) for any participant set U with |U| = k. From (7) and (13), we obtain…”

Section: Contrast Of the Proposed Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel XOR-Based Threshold Visual Cryptography with Adjustable Pixel Expansion

et al. 2020

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“…Researching on image and video related secure issues are important in the field of information security, such as image based data hiding [1][2][3], water marking technologies [4], secure image retrieval [5] or other aspects [6][7][8][9][10]. SIS scheme is an important issue in information security that can protect confidential images among multiple participants.…”

Section: Introductionmentioning

confidence: 99%

Threshold changeable secret image sharing using bivariate polynomial

Liu

Sun

et al. 2020

Preprint

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In secret image sharing (SIS) scheme, a confidential image is encrypted into multiple shadows, any group of shadows that reaches the threshold, otherwise nothing can be reconstructed at all. Most existing SIS schemes have a fixed threshold, however in this work, we consider more complicated cases that the threshold may be adjusted due to the changeable security environment. In this paper, we construct a $(k\leftrightarrow h,n)$ threshold changeable SIS (TCSIS) scheme using bivariate polynomial, which has $h-k+1$ possible thresholds $k,k+1,...,h$. During image reconstruction, each participant can update the his shadow according to the current threshold $T$ only based on his initial shadow. Comparing with previous TCSIS schemes, the proposed scheme achieves unconditional security, and can overcome the information disclosure problem caused by homomorphism.

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“…Intelligent analysis for surveillance technology has been a hot topic in multimedia security community. It is the basis of advanced video processing tasks such as follow-up steganography [1], data hiding [2], JPEG compressed [3] and object recognition [4], and is a necessary prerequisite for implementing highlevel intelligent behavior analysis. Object tracking is one of the fundamental tasks in intelligent surveillance technology.…”

Section: Introductionmentioning

confidence: 99%

Learning Attention for Object Tracking with Adversarial Learning Network

Cheng

Song

et al. 2020

Preprint

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Artificial intelligence has been widely studied on solving intelligent surveillance analysis and security problems in recent years. Although many multimedia security approaches have been proposed by using deep learning network model, there are still some challenges on their performances which deserve in-depth research. On one hand, high computational complexity of current deep learning methods makes it hard to be applied to real-time scenario. On the other hand, it is difficult to obtain the specific features of a video by fine-tuning the network online with the object state of the first frame, which fails to capture rich appearance variations of the object. To solve above two issues, in this paper, an effective object tracking method with learning attention is proposed to achieve the object localization and reduce the training time in adversarial learning framework. First, a prediction network is designed to track the object in video sequences. The object positions of the first ten frames are employed to fine-tune prediction network, which can fully mine a specific features of an object. Second, the prediction network is integrated into the generative adversarial network framework, which randomly generates masks to capture object appearance variations via adaptively dropout input features. Third, we present a spatial attention mechanism to improve the tracking performance. The proposed network can identify the mask that maintains the most robust features of the objects over a long temporal span. Extensive experiments on two large-scale benchmarks demonstrate that the proposed algorithm performs favorably against state-of-the-art methods.

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Detecting Double JPEG Compressed Color Images With the Same Quantization Matrix in Spherical Coordinates

Cited by 49 publications

References 32 publications

A Novel XOR-Based Threshold Visual Cryptography with Adjustable Pixel Expansion

A Novel XOR-Based Threshold Visual Cryptography with Adjustable Pixel Expansion

Threshold changeable secret image sharing using bivariate polynomial

Learning Attention for Object Tracking with Adversarial Learning Network

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