臺灣博碩士論文加值系統

近年來，隨著醫療影像的數位化，醫療影像的保護及認證在醫療機構的資訊傳遞中已愈顯重要。為了避免病人資訊或編號遭到惡意的篡改，在這篇論文中，我們提出了利用基於人類感知技術的數位浮水印方法將病人診療資訊嵌入醫療影像當中，首先利用Perceptual Quality Measure(PQM)並控制臨界值大小將醫療影像分為明顯與不明顯區域，將病人資訊嵌入不明顯區域中以減少醫師的誤判可能。然後使用在離散餘弦轉換(DCT)域下的浮水印方法，來維持加入浮水印後影像的視覺品質及強韌度。實驗顯示出在加入浮水印後影像遭惡意偽造或是一般影像處理，譬如提高對比亮度、清晰化及JPEG壓縮後，在不需要原圖的情況下仍可萃取出病人診療資訊，以達到認證的效果。

Recently, the medical image has been digitized by the development of computer science. The copyright and authentication protection of the medical image is more and more important in medical data transmitting between hospitals. In this paper, we propose a perceptual model based digital watermarking technique for embedding patient information in a medical image. First, we use Perceptual Quality Measure(PQM) method classified a medical image into significant and insignificant regions by controlling the threshold, and embedding patient information in insignificant regions to arise the peak signal to noise ratio(PSNR).Then using a blind image watermarking method in discrete cosine transform(DCT) domain to achieve high quality and robustness of the watermarked images. The experimental results show the watermarked images can extract the watermark clearly by illegal forgery and image processing such as brightness/contrast enhancement, sharpen filtering, adding noise and JPEG lossy compression.

第一章 緒論
1.1 研究動機
1.2 採用之方法
第二章 數位浮水印
2.1 相關技術回顧
2.1.1 空間域浮水印技術
2.1.2 頻率域浮水印技術
2.2 應用於DCT頻率域之浮水印技術
2.2.1 傳統浮水印方法(Cox)
2.2.2 改良傳統浮水印方法(Hsu)
2.2.3 不需原圖來萃取浮水印方法
第三章 基於人類感知對影像的分類
第四章 在DCT域下萃取不需原圖的浮水印技術
第五章 實驗結果與討論
第六章 結論
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