基于辨识性统计特征的PQ隐密图像识别算法

摘要

A PQ (perturbed quantization) stego images recognition algorithm is proposed based on identifiable statistical feature. According to the specific changing ways of PQ steganography to image data, the proposed algorithm extracts the identifiable statistical feature that can distinguish PQ stego images from other types of stego images. Then, the SVM (support vector machines) classifier is trained to recognize PQ stego images. Experimental results show that, the proposed algorithm can reliably recognize PQ stego images from multi-class stego images generated by five types of well-known JPEG steganography (PQ、F5ns、F5、MB1 and MOD). Even though the stego images generated by F5、nsF5、MB1 and MOD are not used for training classifier, the proposed algorithm can still effectively recognize PQ stego images.%提出一种基于辨识性统计特征的PQ（perturbed quantization）隐密图像识别算法。该算法根据经典PQ隐写对图像数据的更改方式，提取可有效区分该类隐密图像与其他类隐密图像的辨识性统计特征，并运用 SVM （support vector machines）分类器进行分类识别。实验结果表明，本算法能够可靠地将PQ隐密图像从5类典型JPEG隐写PQ、F5、nsF5、MB1和MOD的隐密图像中识别出来；即使F5、nsF5、MB1和MOD的隐密图像不参与分类器的训练，本算法仍能有效识别PQ隐密图像。