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Efficient Reversible Data Hiding Based on Prefix Matching and Directed LSB Embedding

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 9023))

Abstract

This paper presents a novel reversible data hiding method, which can recover the original image content without distortion from the stego images after the secret data have been extracted. The method utilizes the original cover image to finally generate two visually similar stego images by embedding additional data. During the data embedding process, the pixels in the first stego image are utilized to embed secret data by applying the proposed prefix matching technique, which exploits each of the gray values to carry one or two bits only with ± 1 operation. Pixels in the second stego image are adaptively modified to carry rest secret data by referring to the first stego image using the directed LSB embedding. For the recipient, the additional data can be extracted from the two stego images with the DH key, and the original cover image can be recovered with the location map. If the cover image has no boundary gray-values, one can always recover the cover image from the two stego images without the aid of any extra information. Experiments show that the proposed method can achieve desirable embedding capacity and maintain a high level of image quality.

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Acknowledgement

This work is supported in part by the National Natural Science Foundation of China (NSFC) under the grant Nos. 61170226, 61170175, the Young Innovative Research Team of Sichuan Province under the grant No. 2011JTD0007, and Chengdu Science and Technology program under the grant No. 12DXYB214JH-002.

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Correspondence to Hongxia Wang .

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Wu, H., Wang, H., Hu, Y., Zhou, L. (2015). Efficient Reversible Data Hiding Based on Prefix Matching and Directed LSB Embedding. In: Shi, YQ., Kim, H., Pérez-González, F., Yang, CN. (eds) Digital-Forensics and Watermarking. IWDW 2014. Lecture Notes in Computer Science(), vol 9023. Springer, Cham. https://doi.org/10.1007/978-3-319-19321-2_35

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  • DOI: https://doi.org/10.1007/978-3-319-19321-2_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19320-5

  • Online ISBN: 978-3-319-19321-2

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