Reversible data hiding in VQ index table with lossless coding and adaptive switching mechanism

In recent years, reversible data hiding (RDH) has attracted extensive attention from the academia. Besides RDH for uncompressed images, RDH for compressed images with satisfactory embedding performance is also important due to the universal use of image compression. In this paper, a RDH scheme for the encoded Vector Quantization (VQ) index table through the Improved Searching Order Coding (ISOC) is proposed. Original image is first compressed with a sorted VQ codebook and further losslessly encoded by the ISOC technique to produce an index table, in which all indices are categorized into three types, i.e., SOC type, Relative Addressing (RA) type and VQ type, based on the relationship between the index and its neighborhood. Each of the first two types of indices is adaptively switched or unchanged according to the current secret bit to be embedded, and the third type of indices isn't used to embed secret data. Experimental results show that, our scheme can embed secret data into 78.396% and 78.377% of all image blocks when VQ codebook sizes equal 256 and 1024, respectively. Compared with the reported schemes, our scheme can achieve higher hiding capacity with lower bit rate and extension degree of index table. A reversible data hiding scheme for the encoded vector quantization (VQ) index table with the improved searching order coding (ISOC) is proposed.Original image is first compressed through a sorted VQ codebook.All indices are categorized into three types, i.e., SOC type, relative addressing (RA) type and VQ type, based on the relationship between the index and its neighboring indices.Each of the SOC and RA types of indices is used to embed 1-bit secret data.The hiding capacity of the proposed scheme is higher than the comparative scheme.

[1]  Cheng-Hsing Yang,et al.  Fractal curves to improve the reversible data embedding for VQ-indexes based on locally adaptive coding , 2010, J. Vis. Commun. Image Represent..

[2]  Robert M. Gray,et al.  An Algorithm for Vector Quantizer Design , 1980, IEEE Trans. Commun..

[3]  Rongrong Ji,et al.  On-Device Mobile Landmark Recognition Using Binarized Descriptor with Multifeature Fusion , 2015, ACM Trans. Intell. Syst. Technol..

[4]  Junqing Yu,et al.  Efficient BOF Generation and Compression for On-Device Mobile Visual Location Recognition , 2014, IEEE MultiMedia.

[5]  Chin-Chen Chang,et al.  Efficient reversible data hiding for VQ-compressed images based on index mapping mechanism , 2013, Signal Process..

[6]  Nasser M. Nasrabadi,et al.  Image coding using vector quantization: a review , 1988, IEEE Trans. Commun..

[7]  Xingming Sun,et al.  Segmentation-Based Image Copy-Move Forgery Detection Scheme , 2015, IEEE Transactions on Information Forensics and Security.

[8]  Doaa Mohammed Image Compression Using Block Truncation Coding , 2011 .

[9]  Bin Li,et al.  General Framework to Histogram-Shifting-Based Reversible Data Hiding , 2013, IEEE Transactions on Image Processing.

[10]  Chin-Chen Chang,et al.  Information hiding based on search-order coding for VQ indices , 2004, Pattern Recognit. Lett..

[11]  Jeffrey J. Rodríguez,et al.  Expansion Embedding Techniques for Reversible Watermarking , 2007, IEEE Transactions on Image Processing.

[12]  Wu-Lin Chen,et al.  Efficient VQ-based image coding scheme using inverse function and lossless index coding , 2013, Signal Process..

[13]  Zhihua Xia,et al.  A Secure and Dynamic Multi-Keyword Ranked Search Scheme over Encrypted Cloud Data , 2016, IEEE Transactions on Parallel and Distributed Systems.

[14]  Chin-Chen Chang,et al.  Reversible data embedding for vector quantization compressed images using search-order coding and index parity matching , 2015, Secur. Commun. Networks.

[15]  Joan L. Mitchell,et al.  JPEG: Still Image Data Compression Standard , 1992 .

[16]  Chin-Chen Chang,et al.  An Inpainting-Assisted Reversible Steganographic Scheme Using a Histogram Shifting Mechanism , 2013, IEEE Transactions on Circuits and Systems for Video Technology.

[17]  Chin-Chen Chang,et al.  A novel VQ-based reversible data hiding scheme by using hybrid encoding strategies , 2013, J. Syst. Softw..

[18]  Michael W. Marcellin,et al.  JPEG2000 - image compression fundamentals, standards and practice , 2002, The Kluwer International Series in Engineering and Computer Science.

[19]  Allen Gersho,et al.  Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.

[20]  Yun Q. Shi,et al.  Reversible Data Hiding , 2003, IWDW.

[21]  Shiuh-Jeng Wang,et al.  VQ Applications in Steganographic Data Hiding Upon Multimedia Images , 2011, IEEE Systems Journal.

[22]  Chaur-Heh Hsieh,et al.  Lossless compression of VQ index with search-order coding , 1996, IEEE Trans. Image Process..

[23]  Jun Tian,et al.  Reversible data embedding using a difference expansion , 2003, IEEE Trans. Circuits Syst. Video Technol..

[24]  Gholamhossein Dastghaibyfard,et al.  A reversible data embedding scheme based on search order coding for VQ index tables , 2011, 2011 8th International ISC Conference on Information Security and Cryptology.

[25]  Chin-Chen Chang,et al.  A fast LBG codebook training algorithm for vector quantization , 1998 .

[26]  Guoping Qiu Color image indexing using BTC , 2003, IEEE Trans. Image Process..

[27]  Nasir Memon,et al.  Secret and public key image watermarking schemes for image authentication and ownership verification , 2001, IEEE Trans. Image Process..

[28]  Junqing Yu,et al.  Projected Residual Vector Quantization for ANN Search , 2014, IEEE MultiMedia.

[29]  Chin-Chen Chang,et al.  Low complexity index-compressed vector quantization for image compression , 1999, IEEE Trans. Consumer Electron..

[30]  Xinpeng Zhang,et al.  Effective reversible data hiding in encrypted image with privacy protection for image content , 2015, J. Vis. Commun. Image Represent..

[31]  Xingming Sun,et al.  Enabling Personalized Search over Encrypted Outsourced Data with Efficiency Improvement , 2016, IEEE Transactions on Parallel and Distributed Systems.