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Xianquan Zhang
Guangxi Key Lab of Multi-Source Information Mining & Security, and Department of Computer Science, Guangxi Normal University, Guilin 541004, China

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Research article
Published: 30 April 2021 in Security and Communication Networks
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Multimedia hashing is a useful technology of multimedia management, e.g., multimedia search and multimedia security. This paper proposes a robust multimedia hashing for processing videos. The proposed video hashing constructs a high-dimensional matrix via gradient features in the discrete wavelet transform (DWT) domain of preprocessed video, learns low-dimensional features from high-dimensional matrix via multidimensional scaling, and calculates video hash by ordinal measures of the learned low-dimensional features. Extensive experiments on 8300 videos are performed to examine the proposed video hashing. Performance comparisons reveal that the proposed scheme is better than several state-of-the-art schemes in balancing the performances of robustness and discrimination.

ACS Style

Zhenjun Tang; Shaopeng Zhang; Zhenhai Chen; Xianquan Zhang. Robust Video Hashing Based on Multidimensional Scaling and Ordinal Measures. Security and Communication Networks 2021, 2021, 1 -11.

AMA Style

Zhenjun Tang, Shaopeng Zhang, Zhenhai Chen, Xianquan Zhang. Robust Video Hashing Based on Multidimensional Scaling and Ordinal Measures. Security and Communication Networks. 2021; 2021 ():1-11.

Chicago/Turabian Style

Zhenjun Tang; Shaopeng Zhang; Zhenhai Chen; Xianquan Zhang. 2021. "Robust Video Hashing Based on Multidimensional Scaling and Ordinal Measures." Security and Communication Networks 2021, no. : 1-11.

Journal article
Published: 18 March 2020 in Applied Sciences
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In this paper, a reversible data hiding method in encrypted image (RDHEI) is proposed. Prior to image encryption, the embeddable pixels are selected from an original image according to prediction errors due to adjacent pixels with strong correlation. Then the embeddable pixels and the other pixels are both rearranged and encrypted to generate an encrypted image. Secret bits are directly embedded into the multiple MSBs (most significant bit) of the embeddable pixels in the encrypted image to generate a marked encrypted image during the encoding phase. In the decoding phase, secret bits can be extracted from the multiple MSBs of the embeddable pixels in the marked encrypted image. Moreover, the original embeddable pixels are restored losslessly by using correlation of the adjacent pixels. Thus, a reconstructed image with high visual quality can be obtained only when the encryption key is available. Since exploiting multiple MSBs of the embeddable pixels, the proposed method can obtain a very large embedding capacity. Experimental results show that the proposed method is able to achieve an average embedding rate as large as 1.7215 bpp (bits per pixel) for the BOW-2 database.

ACS Style

Dewang Wang; Xianquan Zhang; Chunqiang Yu; Zhenjun Tang. Reversible Data Hiding in Encrypted Image Based on Multi-MSB Embedding Strategy. Applied Sciences 2020, 10, 2058 .

AMA Style

Dewang Wang, Xianquan Zhang, Chunqiang Yu, Zhenjun Tang. Reversible Data Hiding in Encrypted Image Based on Multi-MSB Embedding Strategy. Applied Sciences. 2020; 10 (6):2058.

Chicago/Turabian Style

Dewang Wang; Xianquan Zhang; Chunqiang Yu; Zhenjun Tang. 2020. "Reversible Data Hiding in Encrypted Image Based on Multi-MSB Embedding Strategy." Applied Sciences 10, no. 6: 2058.

Journal article
Published: 15 October 2019 in Mathematics
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In this paper, we propose a separable reversible data hiding method in encrypted image (RDHEI) based on two-dimensional permutation and exploiting modification direction (EMD). The content owner uses two-dimensional permutation to encrypt original image through encryption key, which provides confidentiality for the original image. Then the data hider divides the encrypted image into a series of non-overlapping blocks and constructs histogram of adjacent encrypted pixel errors. Secret bits are embedded into a series of peak points of the histogram through EMD. Direct decryption, data extraction and image recovery can be performed separately by the receiver according to the availability of encryption key and data-hiding key. Different from some state-of-the-art RDHEI methods, visual quality of the directly decrypted image can be further improved by the receiver holding the encryption key. Experimental results demonstrate that the proposed method outperforms some state-of-the-art methods in embedding capacity and visual quality.

ACS Style

Chunqiang Yu; Chenmei Ye; Xianquan Zhang; Zhenjun Tang; Shanhua Zhan. Separable Reversible Data Hiding in Encrypted Image Based on Two-Dimensional Permutation and Exploiting Modification Direction. Mathematics 2019, 7, 976 .

AMA Style

Chunqiang Yu, Chenmei Ye, Xianquan Zhang, Zhenjun Tang, Shanhua Zhan. Separable Reversible Data Hiding in Encrypted Image Based on Two-Dimensional Permutation and Exploiting Modification Direction. Mathematics. 2019; 7 (10):976.

Chicago/Turabian Style

Chunqiang Yu; Chenmei Ye; Xianquan Zhang; Zhenjun Tang; Shanhua Zhan. 2019. "Separable Reversible Data Hiding in Encrypted Image Based on Two-Dimensional Permutation and Exploiting Modification Direction." Mathematics 7, no. 10: 976.

Research article
Published: 15 January 2019 in Security and Communication Networks
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Image encryption is a useful technique of image content protection. In this paper, we propose a novel image encryption algorithm by jointly exploiting random overlapping block partition, double spiral scans, Henon chaotic map, and Lü chaotic map. Specifically, the input image is first divided into overlapping blocks and pixels of every block are scrambled via double spiral scans. During spiral scans, the start-point is randomly selected under the control of Henon chaotic map. Next, image content based secret keys are generated and used to control the Lü chaotic map for calculating a secret matrix with the same size of input image. Finally, the encrypted image is obtained by calculating XOR operation between the corresponding elements of the scrambled image and the secret matrix. Experimental result shows that the proposed algorithm has good encrypted results and outperforms some popular encryption algorithms.

ACS Style

Zhenjun Tang; Ye Yang; Shijie Xu; Chunqiang Yu; Xianquan Zhang. Image Encryption with Double Spiral Scans and Chaotic Maps. Security and Communication Networks 2019, 2019, 1 -15.

AMA Style

Zhenjun Tang, Ye Yang, Shijie Xu, Chunqiang Yu, Xianquan Zhang. Image Encryption with Double Spiral Scans and Chaotic Maps. Security and Communication Networks. 2019; 2019 ():1-15.

Chicago/Turabian Style

Zhenjun Tang; Ye Yang; Shijie Xu; Chunqiang Yu; Xianquan Zhang. 2019. "Image Encryption with Double Spiral Scans and Chaotic Maps." Security and Communication Networks 2019, no. : 1-15.

Journal article
Published: 26 November 2018 in IEEE Access
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Reversible data hiding is an important topic of data hiding. This paper proposes a novel separable and error-free reversible data hiding in an encrypted image based on two-layer pixel errors. Specifically, the proposed scheme divides the original image into a series of non-overlapped blocks and permutes these blocks. Then, a closed Hilbert curve is used for scanning each block to obtain a one-dimensional pixel sequence. The pixels of the sequence are encrypted with key transmission. During data hiding, each non-overlapped block of the encrypted image is scanned in the closed Hilbert order to generate a one-dimensional encrypted pixel sequence. Finally, it exploits the histogram of two-layer adjacent encrypted pixel errors to embed secret data by histogram shifting and generate a marked encrypted image. Many experiments are carried out, and the results demonstrate that the proposed scheme reaches a high payload and outperforms some reversible data hiding schemes in the encrypted image.

ACS Style

Chunqiang Yu; Xianquan Zhang; Zhenjun Tang; Xiaojun Xie; Andxiaojun Xie. Separable and Error-Free Reversible Data Hiding in Encrypted Image Based on Two-Layer Pixel Errors. IEEE Access 2018, 6, 76956 -76969.

AMA Style

Chunqiang Yu, Xianquan Zhang, Zhenjun Tang, Xiaojun Xie, Andxiaojun Xie. Separable and Error-Free Reversible Data Hiding in Encrypted Image Based on Two-Layer Pixel Errors. IEEE Access. 2018; 6 ():76956-76969.

Chicago/Turabian Style

Chunqiang Yu; Xianquan Zhang; Zhenjun Tang; Xiaojun Xie; Andxiaojun Xie. 2018. "Separable and Error-Free Reversible Data Hiding in Encrypted Image Based on Two-Layer Pixel Errors." IEEE Access 6, no. : 76956-76969.

Special issue paper
Published: 24 November 2018 in Journal of Real-Time Image Processing
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Reversible data hiding in encrypted image (RDH-EI) is a hot topic of data hiding in recent years. Most RDH-EI algorithms do not reach desirable embedding rate and their computational costs are not suitable for real-time applications. Aiming at these problems, we propose an efficient RDH-EI algorithm with shifting block histogram of pixel differences in homomorphic encrypted domain. A key step of our RDH-EI algorithm is the block-based encryption scheme with additive homomorphism, which can preserve spatial correlation of plaintext image in homomorphic encrypted domain. In addition, our proposed technique of shifting block histogram can achieve efficient data embedding with high payload and correctly recover image. Extensive experiments are conducted to validate performance of our RDH-EI algorithm. Comparison results illustrate that our RDH-EI algorithm outperforms some state-of-the-art algorithms in terms of embedding rate, visual quality and computational time.

ACS Style

Zhenjun Tang; Shijie Xu; Dengpan Ye; Jinyan Wang; Xianquan Zhang; Chuanqiang Yu. Real-time reversible data hiding with shifting block histogram of pixel differences in encrypted image. Journal of Real-Time Image Processing 2018, 16, 709 -724.

AMA Style

Zhenjun Tang, Shijie Xu, Dengpan Ye, Jinyan Wang, Xianquan Zhang, Chuanqiang Yu. Real-time reversible data hiding with shifting block histogram of pixel differences in encrypted image. Journal of Real-Time Image Processing. 2018; 16 (3):709-724.

Chicago/Turabian Style

Zhenjun Tang; Shijie Xu; Dengpan Ye; Jinyan Wang; Xianquan Zhang; Chuanqiang Yu. 2018. "Real-time reversible data hiding with shifting block histogram of pixel differences in encrypted image." Journal of Real-Time Image Processing 16, no. 3: 709-724.

Research article
Published: 04 September 2018 in Security and Communication Networks
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Data hiding in encrypted image is a recent popular topic of data security. In this paper, we propose a reversible data hiding algorithm with pixel prediction and additive homomorphism for encrypted image. Specifically, the proposed algorithm applies pixel prediction to the input image for generating a cover image for data embedding, referred to as the preprocessed image. The preprocessed image is then encrypted by additive homomorphism. Secret data is finally embedded into the encrypted image via modular 256 addition. During secret data extraction and image recovery, addition homomorphism and pixel prediction are jointly used. Experimental results demonstrate that the proposed algorithm can accurately recover original image and reach high embedding capacity and good visual quality. Comparisons show that the proposed algorithm outperforms some recent algorithms in embedding capacity and visual quality.

ACS Style

Chunqiang Yu; Xianquan Zhang; Zhenjun Tang; Yan Chen; Jingyu Huang. Reversible Data Hiding with Pixel Prediction and Additive Homomorphism for Encrypted Image. Security and Communication Networks 2018, 2018, 1 -13.

AMA Style

Chunqiang Yu, Xianquan Zhang, Zhenjun Tang, Yan Chen, Jingyu Huang. Reversible Data Hiding with Pixel Prediction and Additive Homomorphism for Encrypted Image. Security and Communication Networks. 2018; 2018 ():1-13.

Chicago/Turabian Style

Chunqiang Yu; Xianquan Zhang; Zhenjun Tang; Yan Chen; Jingyu Huang. 2018. "Reversible Data Hiding with Pixel Prediction and Additive Homomorphism for Encrypted Image." Security and Communication Networks 2018, no. : 1-13.

Journal article
Published: 01 September 2018 in Neurocomputing
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Color vector angle (CVA) is an important feature of processing color images and has been successfully developed and used in real applications, such as edge detection, indexing and retrieval of images. However, it is unsolved how to apply the CVA to efficiently generating an image hash. Also, most image hashing algorithms choose luminance component of color image for hash generation and cannot well capture the color information of images. To tackle these issues, we study efficient image hashing algorithms with the histogram of CVAs, called HCVA hashing. The histogram is first extracted from those angles that are in the biggest circle inscribed inside the normalized image. And then, it is compressed to make a short hash. We conducted some experiments to assess the performance, and illustrated that the DCT (Discrete Cosine Transform) is the best one of that cooperating with HCVA at generating hashes, as well as the HCVA hashing is robust and promising.

ACS Style

Zhenjun Tang; Xuelong Li; Xianquan Zhang; Shichao Zhang; Yumin Dai. Image hashing with color vector angle. Neurocomputing 2018, 308, 147 -158.

AMA Style

Zhenjun Tang, Xuelong Li, Xianquan Zhang, Shichao Zhang, Yumin Dai. Image hashing with color vector angle. Neurocomputing. 2018; 308 ():147-158.

Chicago/Turabian Style

Zhenjun Tang; Xuelong Li; Xianquan Zhang; Shichao Zhang; Yumin Dai. 2018. "Image hashing with color vector angle." Neurocomputing 308, no. : 147-158.

Article
Published: 28 August 2018 in Multimedia Tools and Applications
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This paper proposes a novel reversible data hiding (RDH) algorithm with differential compression (DC) in encrypted image, which has high embedding capacity. The key contributions are two sides. (1) An efficient block-based encryption scheme is developed for encrypting image. It can transfer spatial correlation between neighboring pixels of plaintext image into encrypted image. (2) The DC scheme is proposed to conduct compression of encrypted image. It can efficiently compress encrypted image by exploiting pixel correlation and vacate a large room for data embedding. Many experiments are conducted to evaluate the performance of our RDH algorithm. Comparisons illustrate that our RDH algorithm outperforms some state-of-the-art algorithms in embedding capacity and computational time.

ACS Style

Zhenjun Tang; Shijie Xu; Heng Yao; Chuan Qin; Xianquan Zhang. Reversible data hiding with differential compression in encrypted image. Multimedia Tools and Applications 2018, 78, 9691 -9715.

AMA Style

Zhenjun Tang, Shijie Xu, Heng Yao, Chuan Qin, Xianquan Zhang. Reversible data hiding with differential compression in encrypted image. Multimedia Tools and Applications. 2018; 78 (8):9691-9715.

Chicago/Turabian Style

Zhenjun Tang; Shijie Xu; Heng Yao; Chuan Qin; Xianquan Zhang. 2018. "Reversible data hiding with differential compression in encrypted image." Multimedia Tools and Applications 78, no. 8: 9691-9715.

Journal article
Published: 04 May 2018 in The Computer Journal
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We propose a novel perceptual image hashing based on weighted discrete wavelet transform (DWT) statistical features. This hashing converts input image into a normalized image by bi-linear interpolation and color space conversion, extracts edge image of the normalized image via Canny operator, and divides the edge image into non-overlapping blocks. For each block, a three-level 2D DWT is applied to obtain different sub-bands and the weighted sum of the DWT statistics of these sub-bands is calculated. Finally, image hash is generated by concatenating and quantizing these weighted DWT features. Similarity of image hashes is measured by Euclidean distance. The Copydays dataset and the Uncompressed Color Image Database (UCID) are both used to evaluate classification between robustness and discrimination. Receiver operating characteristics curve comparisons illustrate that our hashing is superior to some state-of-the-art algorithms in classification performance with respect to robustness and discrimination. The LIVE Image Quality Assessment Database is used to validate our application in reduced-reference image quality assessment. Experimental results show that our hashing has better performance in image quality assessment than two popular measures, i.e. peak signal-to-noise ratio and structural similarity.

ACS Style

Zhenjun Tang; Ziqing Huang; Heng Yao; Xianquan Zhang; Lv Chen; Chunqiang Yu. Perceptual Image Hashing with Weighted DWT Features for Reduced-Reference Image Quality Assessment. The Computer Journal 2018, 61, 1695 -1709.

AMA Style

Zhenjun Tang, Ziqing Huang, Heng Yao, Xianquan Zhang, Lv Chen, Chunqiang Yu. Perceptual Image Hashing with Weighted DWT Features for Reduced-Reference Image Quality Assessment. The Computer Journal. 2018; 61 (11):1695-1709.

Chicago/Turabian Style

Zhenjun Tang; Ziqing Huang; Heng Yao; Xianquan Zhang; Lv Chen; Chunqiang Yu. 2018. "Perceptual Image Hashing with Weighted DWT Features for Reduced-Reference Image Quality Assessment." The Computer Journal 61, no. 11: 1695-1709.

Journal article
Published: 01 March 2018 in Optik
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ACS Style

Zhenjun Tang; Quanfeng Lu; Huan Lao; Chunqiang Yu; Xianquan Zhang. Error-free reversible data hiding with high capacity in encrypted image. Optik 2018, 157, 750 -760.

AMA Style

Zhenjun Tang, Quanfeng Lu, Huan Lao, Chunqiang Yu, Xianquan Zhang. Error-free reversible data hiding with high capacity in encrypted image. Optik. 2018; 157 ():750-760.

Chicago/Turabian Style

Zhenjun Tang; Quanfeng Lu; Huan Lao; Chunqiang Yu; Xianquan Zhang. 2018. "Error-free reversible data hiding with high capacity in encrypted image." Optik 157, no. : 750-760.

Journal article
Published: 01 August 2017 in Signal Processing
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We investigate the use of MDS in image hashing.We propose an MDS-based hashing resistant to any-angle rotation.Rotation-invariant feature matrix is constructed by LPT and DFT.MDS is used to learn a compact and discriminative representation.Our hashing outperforms some state-of-the-art algorithms in classification performance. Multidimensional scaling (MDS) is an efficient technique for data analysis, and has been successfully applied in data visualization, object retrieval, data clustering, and so on. However, its use in image hashing is rarely discussed yet. In this study, we investigate the use of MDS in image hashing and propose an MDS-based hashing algorithm resistant to any-angle rotation. The proposed algorithm extracts a rotation-invariant feature matrix with log-polar transform and discrete Fourier transform from the normalized image, and learns a compact and discriminative representation from the feature matrix by MDS. Experiments with 3845 images are carried out and the results demonstrate that the proposed algorithm is robust to many content-preserving operations, including any-angle rotation, and reaches good discrimination. Receiver operating characteristics (ROC) curve comparisons illustrate that the proposed algorithm outperforms some state-of-the-art algorithms in classification with respect to robustness and discrimination.

ACS Style

Zhenjun Tang; Ziqing Huang; Xianquan Zhang; Huan Lao. Robust image hashing with multidimensional scaling. Signal Processing 2017, 137, 240 -250.

AMA Style

Zhenjun Tang, Ziqing Huang, Xianquan Zhang, Huan Lao. Robust image hashing with multidimensional scaling. Signal Processing. 2017; 137 ():240-250.

Chicago/Turabian Style

Zhenjun Tang; Ziqing Huang; Xianquan Zhang; Huan Lao. 2017. "Robust image hashing with multidimensional scaling." Signal Processing 137, no. : 240-250.

Journal article
Published: 01 September 2016 in Computers & Security
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ACS Style

Zhenjun Tang; Huan Lao; Xianquan Zhang; Kai Liu. Robust image hashing via DCT and LLE. Computers & Security 2016, 62, 133 -148.

AMA Style

Zhenjun Tang, Huan Lao, Xianquan Zhang, Kai Liu. Robust image hashing via DCT and LLE. Computers & Security. 2016; 62 ():133-148.

Chicago/Turabian Style

Zhenjun Tang; Huan Lao; Xianquan Zhang; Kai Liu. 2016. "Robust image hashing via DCT and LLE." Computers & Security 62, no. : 133-148.

Journal article
Published: 13 June 2016 in IETE Technical Review
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Colour space has been widely used in digital image processing, but its selection is rarely discussed in image hashing. Aiming at this problem, we discuss colour space selection by evaluating classification performances of typical hashing algorithms under YCbCr colour space, CIE L*a*b* colour space, HSV colour space, and HSI colour space. Our contributions are two sides. (1) We find that the regularly used YCbCr colour space cannot reach desirable classification performance and HSV colour space outperforms other colour spaces. (2) We analyse classification performances of D-DCT hashing, NMF-NMF-SQ hashing, RT-DCT hashing, and GF-LVQ hashing under different colour spaces, which are the first reports of these algorithms. Receiver operating characteristic graph is used to analyse classification experiments with large data-sets of 2220 similar image pairs and 19,900 different image pairs.

ACS Style

Zhenjun Tang; Xiuqin Li; Juan Song; Minwei Wei; Xianquan Zhang. Colour Space Selection in Image Hashing: An Experimental Study. IETE Technical Review 2016, 34, 440 -447.

AMA Style

Zhenjun Tang, Xiuqin Li, Juan Song, Minwei Wei, Xianquan Zhang. Colour Space Selection in Image Hashing: An Experimental Study. IETE Technical Review. 2016; 34 (4):440-447.

Chicago/Turabian Style

Zhenjun Tang; Xiuqin Li; Juan Song; Minwei Wei; Xianquan Zhang. 2016. "Colour Space Selection in Image Hashing: An Experimental Study." IETE Technical Review 34, no. 4: 440-447.

Journal article
Published: 01 June 2016 in AEU - International Journal of Electronics and Communications
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Image hashing is a novel technology of multimedia processing, and finds many applications, such as image forensics, image retrieval and image indexing. Conventional image hashing algorithms have limitations in reaching desirable classification performances between rotation robustness and discrimination. Aiming at this issue, we propose a robust image hashing based on color vector angle and Canny operator. Specifically, our hashing firstly converts input image to a normalized image by interpolation and Gaussian low-pass filtering. And then, color vector angles and image edges are both extracted from the normalized image. Finally, statistical features incorporating color vector angles and image edges are calculated to form image hash. We conduct experiments with 2762 images to validate efficiency of our hashing. The experimental results show that our hashing is robust against normal digital processing, such as image rotation, brightness/contrast adjustment and JPEG compression, and reaches good discrimination. Receiver operating characteristics (ROC) curve comparisons with some state-of-the-art algorithms indicate that our hashing outperforms these compared algorithms in classification performances between robustness and discriminative capability.

ACS Style

Zhenjun Tang; Liyan Huang; Xianquan Zhang; Huan Lao. Robust image hashing based on color vector angle and Canny operator. AEU - International Journal of Electronics and Communications 2016, 70, 833 -841.

AMA Style

Zhenjun Tang, Liyan Huang, Xianquan Zhang, Huan Lao. Robust image hashing based on color vector angle and Canny operator. AEU - International Journal of Electronics and Communications. 2016; 70 (6):833-841.

Chicago/Turabian Style

Zhenjun Tang; Liyan Huang; Xianquan Zhang; Huan Lao. 2016. "Robust image hashing based on color vector angle and Canny operator." AEU - International Journal of Electronics and Communications 70, no. 6: 833-841.

Journal article
Published: 19 April 2016 in Multimedia Tools and Applications
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We investigate the use of parabolic interpolation in data hiding and propose a novel data hiding algorithm with high capacity based on interpolated image. Specifically, the proposed algorithm creates an interpolated image from input image by parabolic interpolation, and embeds secret bits into interpolated pixels in terms of the relation between the interpolated value and the mean value. Ten standard benchmark images are taken as test images for validating efficiency of our algorithm. The results illustrate that our algorithm has better performances than some popular data hiding methods in embedding capacity and visual quality with respect to PSNR and SSIM.

ACS Style

Xianquan Zhang; Zerui Sun; Zhenjun Tang; Chunqiang Yu; Xiaoyun Wang. High capacity data hiding based on interpolated image. Multimedia Tools and Applications 2016, 76, 9195 -9218.

AMA Style

Xianquan Zhang, Zerui Sun, Zhenjun Tang, Chunqiang Yu, Xiaoyun Wang. High capacity data hiding based on interpolated image. Multimedia Tools and Applications. 2016; 76 (7):9195-9218.

Chicago/Turabian Style

Xianquan Zhang; Zerui Sun; Zhenjun Tang; Chunqiang Yu; Xiaoyun Wang. 2016. "High capacity data hiding based on interpolated image." Multimedia Tools and Applications 76, no. 7: 9195-9218.

Journal article
Published: 30 March 2016 in Multimedia Tools and Applications
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Image encryption is a useful technique of multimedia security and has been widely used in content protection, image authentication, data hiding, and so on. In this paper, we investigate the use of projection partition in image encryption, and then design an efficient image encryption algorithm based on random projection partition and chaotic system. Specifically, our algorithm randomly divides the input image into overlapping blocks. For each block, our algorithm further divides it into a set of projection lines. And then, chaotic system is exploited to generate a secret data pool. Finally, data encryption is done by random projection line swapping and XOR operation between projection line and secret sequence selected from the secret data pool. Many experiments are conducted to validate efficiency of our algorithm. Comparisons are also done and the results show that our algorithm is better than some popular algorithms.

ACS Style

Zhenjun Tang; Fei Wang; Xianquan Zhang. Image encryption based on random projection partition and chaotic system. Multimedia Tools and Applications 2016, 76, 8257 -8283.

AMA Style

Zhenjun Tang, Fei Wang, Xianquan Zhang. Image encryption based on random projection partition and chaotic system. Multimedia Tools and Applications. 2016; 76 (6):8257-8283.

Chicago/Turabian Style

Zhenjun Tang; Fei Wang; Xianquan Zhang. 2016. "Image encryption based on random projection partition and chaotic system." Multimedia Tools and Applications 76, no. 6: 8257-8283.

Journal article
Published: 01 January 2015 in AEU - International Journal of Electronics and Communications
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ACS Style

Xianquan Zhang; Feng Ding; Zhenjun Tang; Chunqiang Yu. Salt and pepper noise removal with image inpainting. AEU - International Journal of Electronics and Communications 2015, 69, 307 -313.

AMA Style

Xianquan Zhang, Feng Ding, Zhenjun Tang, Chunqiang Yu. Salt and pepper noise removal with image inpainting. AEU - International Journal of Electronics and Communications. 2015; 69 (1):307-313.

Chicago/Turabian Style

Xianquan Zhang; Feng Ding; Zhenjun Tang; Chunqiang Yu. 2015. "Salt and pepper noise removal with image inpainting." AEU - International Journal of Electronics and Communications 69, no. 1: 307-313.

Journal article
Published: 01 April 2014 in Applied Mathematics and Computation
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ACS Style

Zhenjun Tang; Xianquan Zhang; Chunqiang Yu; Dan He. Efficient point pattern matching algorithm for planar point sets under transform of translation, rotation and scale. Applied Mathematics and Computation 2014, 232, 624 -631.

AMA Style

Zhenjun Tang, Xianquan Zhang, Chunqiang Yu, Dan He. Efficient point pattern matching algorithm for planar point sets under transform of translation, rotation and scale. Applied Mathematics and Computation. 2014; 232 ():624-631.

Chicago/Turabian Style

Zhenjun Tang; Xianquan Zhang; Chunqiang Yu; Dan He. 2014. "Efficient point pattern matching algorithm for planar point sets under transform of translation, rotation and scale." Applied Mathematics and Computation 232, no. : 624-631.

Article
Published: 01 March 2014 in IET Image Processing
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Colour vector angle has been widely used in edge detection and image retrieval, but its investigation in image hashing is still limited. In this study, the authors investigate the use of colour vector angle in image hashing and propose a robust hashing algorithm combining colour vector angles with discrete wavelet transform (DWT). Specifically, the input image is firstly resized to a normalised size by bi-cubic interpolation and blurred by a Gaussian low-pass filter. Colour vector angles are then calculated and divided into non-overlapping blocks. Next, block means of colour vector angles are extracted to form a feature matrix, which is further compressed by DWT. Image hash is finally formed by those DWT coefficients in the LL sub-band. Experiments show that the proposed hashing is robust against normal digital operations, such as JPEG compression, watermarking embedding and rotation within 5°. Receiver operating characteristics curve comparisons are conducted and the results show that the proposed hashing is better than some well-known algorithms.

ACS Style

Zhenjun Tang; Yumin Dai; Xianquan Zhang; Liyan Huang; Fan Yang. Robust image hashing via colour vector angles and discrete wavelet transform. IET Image Processing 2014, 8, 142 -149.

AMA Style

Zhenjun Tang, Yumin Dai, Xianquan Zhang, Liyan Huang, Fan Yang. Robust image hashing via colour vector angles and discrete wavelet transform. IET Image Processing. 2014; 8 (3):142-149.

Chicago/Turabian Style

Zhenjun Tang; Yumin Dai; Xianquan Zhang; Liyan Huang; Fan Yang. 2014. "Robust image hashing via colour vector angles and discrete wavelet transform." IET Image Processing 8, no. 3: 142-149.