Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/24159
標題: 有關影像認證及還原之研究
A Study of Image Authentication and Recovery
作者: 楊竣崴
Yang, Chun-Wei
關鍵字: Image recovery
影像重建
reversible watermarking technique
random sequence
tamper detection
vector quantization
可還原浮水印技術
隨機序列
竄改偵測
向量量化
出版社: 資訊管理學系所
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摘要: 在目前的浮水印技術中,可以分為二類,一種是強韌型浮水印技術,可以抵抗有心人士的惡意攻擊且取出浮水印;另一種則是易碎型浮水印技術,這種技術也稱為影像認證,在影像傳輸的過程中,偵測影像是否遭受竄改。由於醫學影像、軍事影像等應用,需要很精確而不能有誤差的影像。基於對此應用的需求,在本論文中,我們首先提出了一套新的影像還原方法,其主要精神是將亂數序列之強韌型浮水印技術轉換成可還原的浮水印技術。將目前眾所周知的以亂數序列作為浮水印之強韌型浮水印技術為藏匿方法,配合Sobel邊緣偵測技術找出藏匿影像的邊緣之像素值且保留,最後取代原始影像的對應邊緣位置之像素值,而完成藏匿浮水印之影像。因為強韌型浮水印技術,本來就是利用其可接受影像處理破壞的特性,以達到保護其影像的安全,因此使用我們的方法,雖然損失一些浮水印的資訊,但由實驗結果可驗證其改變後的藏匿影像,沒有造成浮水印偵測的問題。如此一來,不僅可以驗證影像是否有藏匿浮水印,而且能夠達到還原原始影像之目的。 由於可還原的浮水印技術無法得知影像是否遭受竄改與無法承受任何的影像處理攻擊,因此在實際應用上限制其發展空間。且在影像認證技術蓬勃的發展中,主要研究都為了改善影像認證的強韌性與偵測能力,因此忽略影像重建這部份。所以本篇論文接著提出一套影像竄改偵測與重建的技術,首先將影像的像素值做隨機亂數的處理,使得全部的像素值重新排序,則可得到像素值對應藏匿位置之關係。亂數處理是為了避免讓有心人士,輕易就找出影像的重建資訊。接著將原始影像做向量量化編碼得到索引表,當作影像特徵再藏匿至原始影像中,爾後將藏匿的索引表取出即可用於重建影像毀損之部份。最後結合王學者的浮水印技術進行竄改偵測,達到影像認證與重建之目的。 總結我們所提出的方法,主要是利用王學者的浮水印技術,以準確的標示出被竄改的區域。若影像判定遭受竄改,則利用向量量化壓縮後的索引表重建影像被竄改的區域。雖然影像重建技術無法使得重建影像與原始影像完全一樣,但接收者可在收到影像後,找出竄改部份且立即重建該影像內容,使得重建後影像品質與原始影像很相似,便可節省影像重新傳輸的頻寬與時間。根據相關實驗結果證實,本論文所提出的第一個技術只需額外付出平均約5.61 K bytes很少的還原資訊即可達到影像還原的目的。此外在第二個技術中,我們的方法不僅增加影像特徵的藏匿次數,達到提升影像重建的機率,而且影像邊緣的部份亦有較好之重建品質。
Today's watermarking techniques can be divided into two types. The first type is robust watermarking technique which can resist malicious attacks better. The second type is fragile watermarking technique, also called image authentication, can verify whether the image is tampered in the process of image transfer or not. There are some applications requires accurate images such as medical or military images which users need to employ original images. Based on those specific requirements, we proposed a scheme of image recovery. The first proposed scheme improves the robust digital watermarking technique based on random sequence into reversible watermarking technique. Therefore, this method will use the robust watermarking technique of the well-known random sequence as embedding approach. Sobel edge detection technique is employed to extract the pixel value of edges from the watermarked image. And the final watermarked image is produced by replace the original image corresponding to the pixel value of the edges for the purpose of embedding watermark. Because the robust watermarking technique can tolerate the image which is destroyed to protect the copyright, there is no watermarking examination problem although this approach causes some loss of watermark information according to the experiment result. Moreover, it can not only examine whether the image has embedded watermarks, but also restore the original image. Majority of researches related to the image authentication are mainly focusing on improving the robustness and the ability of tamper detection on image authentication. The practical application of restrictions on reversible watermarking technique, which can't tolerate any image processing attack, neither can tell whether the image is tampered or not. Nevertheless, image recovering is also an important issue. We proposed an image tamper detection and recovery method, which can recovery image effectively, especially for images with large tampered regions. First, a secret key is used to obtain a random sequence and determine where to embed watermarks on the basis of this random sequence. As a result, it is hard to find out the corresponding location of watermarks from embedded images. Later, through vector quantization, we create an index table as a basis for recovery and embed it in the original image. Finally, Wong's watermarking scheme is integrated to perform tamper detection and achieve image authentication and recovery. Summary of our method, Wong's watermarking scheme is employed to perform tamper detection. Wong's watermarking scheme can be used to accurately locate tampered regions. If an image has been tampered, the index table can be used to recover the tampered regions. Although the image recovery technique unable to restore the image completely, receiver can identify the tampered locations and recovery immediately, as it will save additional bandwidth to retransmit the image. According to the experiment results, the first method we propose only needs to pay 5.61 k bytes overheads in average for restoring original images. Besides, the second method has the higher probability of image recovery and our scheme provides not only a better quality of recovered images but also better results at edge regions.
URI: http://hdl.handle.net/11455/24159
其他識別: U0005-1407200900124000
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-1407200900124000
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