Perceptual Hashing With Visual Content Understanding for Reduced-Reference Screen Content Image Quality Assessment

Huang, Ziqing; Liu, Shiguang

doi:10.1109/tcsvt.2020.3027001

Cited by 36 publications

(17 citation statements)

References 56 publications

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“…Thus, V = V because G 2 = G 2 . According to the formula (11), the projection matrix of the translated matrix B j is as follows.…”

Section: New Property Of Translation Invariancementioning

confidence: 99%

“…It is a useful technology of image representation for improving efficiencies of data processing of massive images. In practice, image hashing has been applied to numerous fields [9], [10], [11], such as copy detection, screen quality assessment, tampering detection and social hot event detection. Generally, image hashing needs to meet two essential performance indicators [12], [13], [14], namely, robustness and discrimination.…”

Section: Introductionmentioning

confidence: 99%

“…(2) Discrimination. Discrimination is also called anticollision [11], [13]. It means that, for images with different contents, hashing method ought to compress them into different hash sequences.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Efficient Hashing Method Using 2D-2D PCA for Image Copy Detection

Liang

Tang

Huang

et al. 2023

IEEE Trans. Knowl. Data Eng.

Self Cite

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Image copy detection is an important technology of copyright protection. This paper proposes an efficient hashing method for image copy detection using 2D-2D (two-directional two-dimensional) PCA (Principal Component Analysis). The key is the discovery of the translation invariance of 2D-2D PCA. With the property of translation invariance, a novel model of extracting rotation-invariant lowdimensional features is designed by combining PCT (Polar Coordinate Transformation) and 2D-2D PCA. The PCT can convert an input rotated image to a translation matrix. Since the 2D-2D PCA is invariant to translation, the low-dimensional features learned from the translation matrix are rotation-invariant. Moreover, vector distances of low-dimensional features are stable to common digital operations and thus hash construction with the vector distances is of robustness and compactness. Three open image datasets are exploited to conduct various experiments for validating efficiencies of the proposed method. The results demonstrate that the proposed method is much better than some representative hashing methods in the performances of classification and copy detection.

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“…Thus, V = V because G 2 = G 2 . According to the formula (11), the projection matrix of the translated matrix B j is as follows.…”

Section: New Property Of Translation Invariancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Efficient Hashing Method Using 2D-2D PCA for Image Copy Detection

Liang

Tang

Huang

et al. 2023

IEEE Trans. Knowl. Data Eng.

Self Cite

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show abstract

“…Consequently, there is a huge number of images/videos in cyberspace [1], and it is a challenge to detect similar copies from massive images/videos [2,3]. To handle this problem, many researchers proposed to use hashing algorithms [4][5][6][7][8][9] to efficiently process multimedia data.…”

Section: Introductionmentioning

confidence: 99%

Efficient video hashing based on low‐rank frames

Chen

Tang

Zhang

et al. 2021

IET Image Processing

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Video hashing is a useful technology for diverse video applications, such as digital watermarking, copy detection and content authentication. This paper proposes a novel efficient video hashing based on low-rank frames. A key contribution is the low-rank frame calculation using the low-rank approximation of singular value decomposition (SVD). As the large singular values of SVD are stable to digital operations, video hash extraction using low-rank frames can provide good robustness. Since most energy is contained within the large singular values, low-rank frames also contribute to discrimination. Moreover, two-dimensional discrete wavelet transform (DWT) is applied to every low-rank frame and the mean of low-frequency DWT coefficients is selected as a hash element. Since these coefficients can represent input data approximately, hash discrimination is thus ensured. Experiments with 16,850 videos are carried out to test performances of the proposed algorithm. The results show that the proposed algorithm outperforms some well-known video hashing algorithms in computational time and classification about discrimination and robustness.

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“…Shen et al [9] extracted the color opposition component from the secondary image and applied quadtree decomposition to connect the generated color feature vector with the structural feature vector and then combined with pseudo-random key scrambling to generate the final hash sequence. For the content of image in screen, the scheme in [10] extracted the maximum gradient and the corresponding direction information from R, G, and B color components and counted the relevant data to construct the image hash sequence.…”

Section: Introductionmentioning

confidence: 99%

Perceptual Image Hashing Based on Multitask Neural Network

Xiong

Liu

et al. 2021

Security and Communication Networks

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With the advent of the era of multimedia and in-depth development, the whole human society has been produced and spread a huge amount of image data, but at the same time, in view of the digital image and tamper with the attack of piracy phenomenon also more and more serious, malicious attacks will produce serious social, military, and political influence, therefore, to protect the authenticity of the original image content, which is also more and more important. In order to further improve the performance of image hashing and enhance the protection of image data, we proposed an end-to-end dual-branch multitask neural network based on VGG-19 to produce a perceptual hash sequence and used prepart of network of pretrained VGG-19 model to extract image features, and then, the image features are transformed into a hash sequence through a convolutional and fully connected network. At the same time, in order to enhance the function of the network and improve the adaptability of the proposed network to using scenarios, the rest part of the network layer of the VGG-19 model was used as another branch for image classification, so as to realize the multitask characteristics of the network. Through the experiment of the testing set, the network can not only resist many kinds of attack operations (content retention operations), but also realize accurate classification about the image, and has a satisfactory tampering detection ability.

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Perceptual Hashing With Visual Content Understanding for Reduced-Reference Screen Content Image Quality Assessment

Cited by 36 publications

References 56 publications

Efficient Hashing Method Using 2D-2D PCA for Image Copy Detection

Efficient Hashing Method Using 2D-2D PCA for Image Copy Detection

Efficient video hashing based on low‐rank frames

Perceptual Image Hashing Based on Multitask Neural Network

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