Exploring the location of object deleted by seam-carving

Seam-carving is used for adjusting the size of an image as well as removing objects from images. When seam-carving is applied to delete the object in the image, it may lead to the distortion of the information transmitted by the image, misleading the public, and endangering human health. Therefore, detecting the location of objects removed by seam-carving techniques is a scientific challenge to the image forensics. According to the position movement law of the related pixel in the seam-carving process, a method of the detecting and locating the objects deleted based on the block artifact grid (BAG) mispairing characteristic is proposed in this paper. Firstly, the BAG is extracted from the JPEG image; secondly, 10-dimensional features of the BAG chart is constructed; thirdly, clustering technique is applied on the extracted features of the BAG to obtain the classification results; finally, the location of the removed object is computed based on the previous classification results. Experiment result shows that the proposed method can efficiently detect and locate the object removed from an image by seam-carving. The proposed method in this paper opens up a new research direction for the location and detection of tampering, and has important application value for the intelligent forensics system based on seam carving.