Detection of double-compression for applications in steganography

This paper presents a method for detection of double JPEG compression and a maximum likelihood estimator of the primary quality factor. These methods are essential for construction of accurate targeted and blind steganalysis methods for JPEG images. The proposed methods use support vector machine classifiers with feature vectors formed by histograms of low-frequency DCT coefficients. The performance of the algorithms is compared to prior art on a database containing approximately 1, 200, 000 images.