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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