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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Main Authors: CHEN, YING-CHING, 陳映親
Other Authors: LEE, JUNG-SANG
Format: Others
Language:en_US
Published: 2018
Online Access:http://ndltd.ncl.edu.tw/handle/z482rv
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spelling 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
collection NDLTD
language en_US
format Others
sources NDLTD
description 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).
author2 LEE, JUNG-SANG
author_facet 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
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AT chényìngqīn jīyúzìshìyīngxiàngsùyǐncángzhīkěkuòchōngjīmìyǐngxiàngfēnxiǎngjìshù
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