JPEG image width estimation for file carving

Abstract

Image width is an important factor for making the partially recovered data perceptually meaningful in image file carving. The authors conduct a comprehensive comparison of the performance of the representative methods for estimating the JPEG image width. Experimental results show that the best methods based on pixels are always better than the best methods based on quantised discrete cosine transform (DCT) coefficients. To keep the good performance of the pixel-based methods when the correct quantisation tables are unavailable, the authors replace the correct quantisation tables with the standard ones. Experimental results certify that such a replacement has only a little effect on the performance of the pixel-based methods, the best of which still outperform the best methods based on quantised DCT coefficients. The two results indicate that it may be enough to just focus on the pixel-based methods for future work. Finally, they propose a pixel-based method, which derives the candidate image widths from the most likely adjacent minimum coded unit (MCU) pairs in the vertical direction. The candidate width which appears most frequently is chosen as the estimated image width. Experimental results show that the proposed method usually has the best performance when most MCUs of an image are recovered.

A Meta-Heuristic Method for Reassemble Bifragmented Intertwined JPEG Image Files in Digital Forensic Investigation

“…The proposed method is to find fragmentation points using a binary search algorithm and then generate several options to reassemble the JPEG image based on the size of the fragments. Wu et al [17] propose a Pixel-based method to estimate image width, which is essential in image recovery. To estimate the JPEG image width, the proposed method derives the candidate image widths from the adjacent Minimum Coding Units (MCUs) pairs in the vertical boundary.…”