Contrast Modification Forensic Algorithm Based on Superpixel and Histogram of Run Length
Funds:
Tianjin Natural Science Foundation (16JCYBJC 15700)
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摘要: 該文提出一種基于超像素和游程直方圖的圖像對比度修改檢測取證算法。算法首先對圖像進行超像素分割，并提取每個分割區(qū)域的游程直方圖特征值，然后將不同方向的特征值進行融合，并進行歸一化處理；再計算處理后的特征值數值突變量；最后將區(qū)域的數值突變量用支持向量機(SVM)進行分類識別。實驗結果表明，和現有的一些算法相比，該文提出的算法計算復雜度低，在多種不同的測試數據庫上都具有良好的識別性能。此外，在區(qū)域篡改檢測實驗中，該算法不僅可以定位出篡改區(qū)域，還能準確地描繪出篡改區(qū)域的輪廓形狀。Abstract: A novel image forensic algorithm against contrast modification based on superpixel and histogram of run length is proposed. In the proposed algorithm, images are firstly divided by superpixel, then run length histogram features of each block are extracted, and those of different orientation are subsequently merged. After normalization of the prior features, the leaps in the histogram are calculated numerically. Lastly, the generated features of blocks are trained by Support Vector Machin (SVM) classifier. Large amounts of experiments show that, the proposed algorithm has low cost of computation complexity. And compared with some state-of-the-art algorithms, it has better performance with many test databases. Furthermore, the proposed algorithm can not only located the tempered area, but also can exactly describe the shape of tempered area.
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