Using Patch Analysis Methods to Detect Images Tampered with Seam Insertion

Peiyu Jiang, Hui-Jun Cheng, Jyh-Da Wei · 2015

Retargeting images by seam carving and seam insertion is hard to identify; therefore, detection of seam tampered images has been an important but challenging research topic. Aside from existing methods, i.e., those derived from steganography attacks and those based on statistical features, we have proposed a novel detection method in our previouswork, referred to as the patch analysis method. This method divides images into 2 × 2 blocks, named as mini-squares, and then searches for one of nine patch types that is likely to recover a mini-square from seam carving. By analyzing the patch transition probability among three-connected mini-squares, we achieved currently best accuracies for detecting seam carved images. Here we extend the application of this method to detect imagestampered with seam insertion. We will present and discuss the experimental results in this paper.

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