Scalable Secret Image Sharing based on Adaptive Pixel-embedding Technique
碩士 === 逢甲大學 === 資訊工程學系 === 106 === Different from secret image sharing technique, the secret of a scalable secret image sharing is displayed in the way that it could be progressively recovered by a set of shares. In other word, incomplete gathering of shadows cannot be used to reconstruct the whole...
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ndltd-TW-106FCU003920112019-06-27T05:27:53Z http://ndltd.ncl.edu.tw/handle/z482rv Scalable Secret Image Sharing based on Adaptive Pixel-embedding Technique 基於自適應像素隱藏之可擴充機密影像分享技術 CHEN, YING-CHING 陳映親 碩士 逢甲大學 資訊工程學系 106 Different from secret image sharing technique, the secret of a scalable secret image sharing is displayed in the way that it could be progressively recovered by a set of shares. In other word, incomplete gathering of shadows cannot be used to reconstruct the whole image S immediately. To improve the security of SSIS, Lee and Chen have designed a selective scalable secret image sharing mechanism (SSSIS) to reduce the awareness of malicious attackers. Nevertheless, the quality of Lee and Chen’s scheme is not good due to the image distortion and storage overhead of static embedding. Thus, we introduce the concept of adaptive pixel-embedding into SSSIS, in which the embedded bits could be uniformly distributed in the stego image. Aside from the human vision perception, experimental results have demonstrated the superiority of new method over related works in terms of two objective indexes, including peak signal to noise ratio (PSNR) and structural similarity (SSIM). LEE, JUNG-SANG 李榮三 2018 學位論文 ; thesis 22 en_US |
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碩士 === 逢甲大學 === 資訊工程學系 === 106 === Different from secret image sharing technique, the secret of a scalable secret image sharing is displayed in the way that it could be progressively recovered by a set of shares. In other word, incomplete gathering of shadows cannot be used to reconstruct the whole image S immediately. To improve the security of SSIS, Lee and Chen have designed a selective scalable secret image sharing mechanism (SSSIS) to reduce the awareness of malicious attackers. Nevertheless, the quality of Lee and Chen’s scheme is not good due to the image distortion and storage overhead of static embedding. Thus, we introduce the concept of adaptive pixel-embedding into SSSIS, in which the embedded bits could be uniformly distributed in the stego image. Aside from the human vision perception, experimental results have demonstrated the superiority of new method over related works in terms of two objective indexes, including peak signal to noise ratio (PSNR) and structural similarity (SSIM).
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LEE, JUNG-SANG |
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LEE, JUNG-SANG CHEN, YING-CHING 陳映親 |
author |
CHEN, YING-CHING 陳映親 |
spellingShingle |
CHEN, YING-CHING 陳映親 Scalable Secret Image Sharing based on Adaptive Pixel-embedding Technique |
author_sort |
CHEN, YING-CHING |
title |
Scalable Secret Image Sharing based on Adaptive Pixel-embedding Technique |
title_short |
Scalable Secret Image Sharing based on Adaptive Pixel-embedding Technique |
title_full |
Scalable Secret Image Sharing based on Adaptive Pixel-embedding Technique |
title_fullStr |
Scalable Secret Image Sharing based on Adaptive Pixel-embedding Technique |
title_full_unstemmed |
Scalable Secret Image Sharing based on Adaptive Pixel-embedding Technique |
title_sort |
scalable secret image sharing based on adaptive pixel-embedding technique |
publishDate |
2018 |
url |
http://ndltd.ncl.edu.tw/handle/z482rv |
work_keys_str_mv |
AT chenyingching scalablesecretimagesharingbasedonadaptivepixelembeddingtechnique AT chényìngqīn scalablesecretimagesharingbasedonadaptivepixelembeddingtechnique AT chenyingching jīyúzìshìyīngxiàngsùyǐncángzhīkěkuòchōngjīmìyǐngxiàngfēnxiǎngjìshù AT chényìngqīn jīyúzìshìyīngxiàngsùyǐncángzhīkěkuòchōngjīmìyǐngxiàngfēnxiǎngjìshù |
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