基於影像不變特徵及區域離群值檢測之重複區域偵測

Region Duplication Detection Based on Image Invariant Feature and Local Outlier Detection

黃偲能(Ssu-Neng Huang)

指導教授 ： 郭天穎

國立臺北科技大學/電資學院/電機工程系研究所/碩士(2011年)

摘要

近年來，先進影像編輯軟體快速的發展，使得數位影像容易遭受到篡改，人眼並不易察覺到篡改的痕跡；因此，需設計一演算法，自動偵測出遭受篡改之區域。區域複製(Region Duplication)是一種常見且簡單的數位影像篡改方式，針對此種篡改方式，目前的文獻方法對於影像原有之相似重複物件(intrinsic repeated elements)，皆易誤判為複製的區域(duplicated region)；另外，文獻中基於稀疏特徵描述子(sparse feature descriptor)之匹配方法雖能偵測出幾何、亮度變化之複製區域，但對於受到較大的仿射形變或旋轉複製區域，偵測結果仍不甚佳。
本論文強化稀疏特徵描述子方法，以提升幾何、亮度變化之數位影像複製區域篡改偵測能力，我們同時基於此影像不變特徵(image invariant feature)之分佈特性，提出區域離群值檢測(local outlier detection)方法，解決影像之原有重複區域(intrinsic repeated region)的誤判問題。我們自動產生帶有幾何、亮度變化等區域複製篡改影像進行準確度評估，實驗中同時考慮含有影像原有之相似重複物件的圖片，證實所提出之方法具有強健性，能夠有效偵測出複製區域。

關鍵字

影像鑑識 ； 篡改偵測 ； 重複區域偵測 ； SIFT ； SURF ； 區域離群值

並列摘要

Nowadays image editing software is so sophisticated that one can easily tamper digital images without leaving any obvious traces. To develop an automatic tampering detection algorithm becomes an important issue. Region duplication is a common and simple way of digital image tampering. Recent methods based on sparse feature descriptor matching can detect the region duplication with lower geometrical and illumination distortion, where past methods could fail, but they are still imperfect for the detection of duplicated regions imposed with stronger distortion of affine transform and rotation. Furthermore, all the existing methods will mistakenly classify the intrinsic repeated elements as duplication tamping.
Our method stems from sparse feature descriptor matching approach. We propose a new matching method for higher distortion and a local outlier detection method to analyze the distribution of image invariant feature on image space for intrinsic repeated elements. We evaluate our proposed approach on a set of automatically synthesized forgery images with duplicated, distorted regions and intrinsic repeated elements. The experimental results show that our proposed method is robust and effective in region duplication detection.

並列關鍵字

Image forensics ； tampering detection ； duplication region detection ； sparse feature descriptor ； local outlier detection

參考文獻

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[5] T. V. Lanh, K. S. Chong, S. Emmanuel and M. S. Kankanhalli, “A Survey on Digital Camera Image Forensic Methods,” IEEE International Conference on Multimedia and Expo, pp. 16-19, Jul. 2007.