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    請使用永久網址來引用或連結此文件: https://ir.lib.ncu.edu.tw/handle/987654321/106874


    題名: Image Steganography Using Gradient Adjacent Prediction in Side-Match Vector Quantization
    作者: 王尉任;Tsui, Shiau-Rung;Huang, Cheng-Ta;Wang, Wei-Jen
    貢獻者: 資訊電機學院資訊工程學系
    關鍵詞: Artificial intelligence;Gradient adjacent prediction (GAP);SMVQ;Steganography
    日期: 2013-06-28
    上傳時間: 2026-04-23 13:47:24 (UTC+8)
    出版者: Springer Verlag;Germany: Springer Berlin / Heidelberg
    摘要: 摘要: This study presents a new steganographic method that embeds secret data into a cover digital image using VQ encoding. The core concept of the proposed method uses the gradient adjacent prediction (GAP) algorithm, which enhances prediction accuracy of neighboring blocks in SMVQ encoding. To embed secret data into the cover image, the proposed method utilizes the features of GAP to decide the capacity of the secret data per pixel in a block. It then embeds the secret data accordingly. It also embeds an index value in each block to ensure that the secret data can be recovered back. The index value points to the closest codeword of a state codebook to the encoding block, where the state codebook is generated by GAP-based SMVQ. The result shows that the proposed method has better performance than a recent similar work proposed by Chen and Lin in 2010.
    出版者: Germany: Springer Berlin / Heidelberg
    出版日期: 2013
    出處: Advances in Intelligent Systems and Applications - Volume 2, 2013, p.121-129
    版權: Springer-Verlag Berlin Heidelberg 2013
    識別號: ISSN: 2190-3018
    識別號: ISBN: 9783642354724
    識別號: ISBN: 3642354726
    識別號: EISSN: 2190-3026
    識別號: EISBN: 9783642354731
    識別號: EISBN: 3642354734
    識別號: DOI: 10.1007/978-3-642-35473-1_13
    識別號: OCLC: 823728185
    識別號: LCCallNum: Q342
    顯示於類別:[資訊工程學系] 期刊論文

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