結論

經過長期的研究發展，至今已有相當多的數位影像浮水印技術被提出。目前 的數位影像浮水印研究趨勢大多偏向於具有高強韌性的轉換域演算法為主，學者 們對於空間域演算法的研究意願則逐漸減少。浮水印強韌性低是一般空間域演算 法的通病，而且非常難以改良，使得空間域演算法的研究者們大都轉而研究如何 提升空間域演算法的浮水印可嵌入容量，或是改採較不具實用性的非盲式方法，

企圖提高浮水印的抗攻擊能力。

為了改善空間域演算法在強韌性方面的嚴重缺陷，本論文提出一個以區域像 素平均值為門檻值之區域像素二值化方法，結合互斥或運算子之運算特性進行分 析及嵌入浮水印。透過調整擁有切割區塊最小差異量的灰階值的做法，可使浮水 印的嵌入動作對原始掩護影像造成的失真影響降低。本論文方法在嵌入過程同時 建立金鑰，使偽裝掩護影像在遭受各種影像處理攻擊之後仍能藉由金鑰的輔助擷 取出正確率較高的浮水印影像。本研究方法所採用的二元浮水印影像在嵌入之前 會進行偽隨機編碼的保護動作，藉此提高浮水印資訊的安全性。本論文方法的浮 水印擷取程序不需參考任何原始掩護影像的資訊，故屬於高實用性的盲式演算 法。

本論文所使用的浮水印嵌入方法屬於直接對原始掩護影像灰階值進行修改 的空間域演算法，不需要如轉換域演算法那般繁雜的數學運算與轉換程序。經由 實驗測試，本論文方法執行完整的浮水印嵌入及擷取動作只需耗費約 1.4 秒的運 算時間，不但能節省運算成本，且能更便捷地為使用者所用。

一個具備正常功能的浮水印演算法必須能應用在不同的掩護影像上，並且能 保持其原有之效能。本研究中採用了 4 張不同的原始掩護影像進行通用性測試。

經實驗結果證明，本研究方法應用在不同的原始掩護影像上皆擁有不錯的隱蔽性 效能，故可知本研究方法確實能通用於不同的掩護影像上。

本方法與同樣使用互斥或運算子進行浮水印嵌入動作的 Wu 等人[32]以及 Zhang 和 Shih[39]所提出的方法進行實驗測試比較，結果顯示本方法對原始掩護 影像的品質破壞相當低，隱蔽性評估結果也優於其他兩種比較方法；在浮水印強 韌性方面，即使本方法的浮水印抗攻擊能力仍有相當大的改善空間，但相對其他 兩種比較方法擷取之低品質浮水印而言，本方法已將無法以肉眼辨識之擷取浮水 印影像品質改善至可由人眼進行識別的狀態。由此可知本方法確實能夠改善空間 域嵌入法在浮水印強韌性方面的缺陷，並且保有空間域嵌入法隱蔽性高以及計算 複雜度低的優點。

本研究方法未來的改良方向有：

(a) 提升浮水印可嵌入容量：

本研究方法需限制浮水印的大小為掩護影像大小的 1/16，但一般的空間域嵌 入法往往擁有比本方法還要大上許多的浮水印可嵌入容量，如此才能提供給 使用者更多的空間用以隱藏浮水印資訊，因此如何提高本方法的浮水印可嵌 入容量便成為未來的改良目標之一。

(b) 減少受保護影像之外的資料容量耗費：

本研究方法的浮水印擷取程序需輔以四筆金鑰資訊與一筆二元混亂矩陣資 訊分別作為提升擷取正確率及解密浮水印之用，總共需五筆與浮水印大小相 同之輔助資訊才能擷取出擁有較高品質的浮水印影像，並保有其安全性。因 此，如何減少這些輔助資訊所造成的資料容量耗費便成為本研究方法未來的 改善目標之一。

(c) 提升浮水印的抗攻擊能力：

雖然本方法的浮水印強韌性相較於 Wu 等人[32]以及 Zhang 和 Shih[39]所提 出的方法，幾乎都有顯著的改良效果，並且能承受更多樣化的影像處理攻 擊。但受攻擊後的擷取浮水印影像大多僅有人眼勉強可辨識的品質，整體浮

水印影像仍然相當模糊，擷取正確率也僅落於 70 至 80 個百分點間居多，故 如何更加提升浮水印的抗攻擊能力且保存現有的高隱蔽性效能與低計算量 特性便成為本方法未來的主要改善方向。

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