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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/35155

    Title: Lossy compression-tolerant data hiding
    Other Titles: 可以忍受失真壓縮處理的資訊隱藏技術
    Authors: 高泉合;Kao, Chuan-ho
    Contributors: 淡江大學資訊工程學系博士班
    施國琛;Shih, Timothy K.
    Keywords: 資訊隱藏;VQ;JPEG;圖形失真壓縮;Data Hiding;VQ;JPEG;Lossy Image Compression
    Date: 2005
    Issue Date: 2010-01-11 06:05:19 (UTC+8)
    Abstract: 在網際網路快速發展的時代中,資訊在公開網路上傳遞的數量也越來越多,有時候我們並不希望我們所傳遞的重要資訊或資料,被其他不相關的人所檢閱,因此漸漸的有了加解密技術的產生,但是只靠加解密技術已經不再能夠滿足現在的需求,因為加解密後所得的資訊會變為亂碼,在網路上傳遞亂碼不就是告訴大家這是重要的資訊,所以如果我們可以將亂碼隱藏在一份有意義的資料中,欺騙過破壞或偷窺者,便可以解決這樣的顧慮,在這篇論文中所提出的方法就是在於解決這方面問題,可以讓使用者將他們所要傳遞的重要資訊隱藏在一張圖形中,讓其他人誤會使用者只是在傳遞一張不重要的圖形,事實上裡面藏有其他重要的資訊。

    Lossy compression-tolerant data hiding methods are proposed in this thesis. Data hiding hides the confidential data secretly. The unauthorized people are difficult to detect hidden data. It provides a secure channel to transmit confidential information. Nowadays, it is a very important technique when we are progressively going to computer network age. There are many hiding method that have proposed. But the most of methods will lost an amount of hiding data after do the lossy compression process. However, there are few people will transmit no lossy compression image in the public internet. When people use our method, the receiver can extracts complete data correctly from the lossy compression image. It is fit to hide text data and transmit image in public internet environment now. The propose methods hide data in an image in conjunction with a lossy compression. The image which hides data is called a stego-image. The reverse algorithm extracts data correctly after receiving the stego-image (i.e., the image which hides data). Our mechanism saves the amount of data transmitted on the Internet. Also, it is difficult for human visual system to detect the difference between the original image and the steog-image. Besides, it can speed up transmission of stego-images and is regular that transmit lossy compression image on the internet now.
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Thesis

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