Enhanced resampling detection based on image correlation of 3D stereoscopic images

Choi et al. EURASIP Journal on Image and Video Processing (2017) 2017:22 DOI 10.1186/s13640-017-0170-9 EURASIP Journal on Image and Video Processing R ES EA R CH Open Access Enhanced resampling detection based on image correlation of 3D stereoscopic images Hak-Yeol Choi, Dai-Kyung Hyun, Sunghee Choi and Heung-Kyu Lee* Abstract In this paper, we propose a resampling detection method for stereoscopic images. Although previous resampling techniques can be applied to stereoscopic images, performance improvement is hard to be expected with the two separated results. In this research, we found a strong relationship between the left and right images derived from the characteristics of the stereoscopic images. The proposed technique exploits that relationship of the stereoscopic images as additional information for reliable detection performance. Furthermore, the proposed method includes a preprocessing step to acquire the independent performance from the image’s own characteristics. The experimental results exhibit superior performance compared with the existing works. Keywords: Multimedia forensic, Resampling detection, Stereoscopic images, Visual fatigue 1 Introduction With recent rapid developments in technology, digital content can now be generated anytime and anywhere by electronic devices such as smartphones, digital cameras, and CCTVs. At the same time, a significant volume of this content is being shared through various media such as social networks and broadcasting channels. Some content is used for important purposes such as evidence in court or as a medium for communicating political issues. If such important digital content is illegally tampered, it may cause severe socio-economic loss. In the past, suspicious modulation of content was analyzed by human judgment. However, computer graphics technology has been advanced tremendously over the decades, and distinguishing a tampered image from an original image has become a harder job. Multimedia forensic is a set of technologies to overcome the limitations of human-based forgery analysis. Since multimedia forensics relies on underlying statistical properties to reveal tampering, the forgery can be detected even if the traces are not visible to human eyes. Also, power of computer allows tens of thousands of content files to be analyzed automatically. *Correspondence: School of Computing, Korea Advanced Institute of Science and Technology, 291, Daehak-Ro, Yuseong-gu, Daejeon 34141, Republic of Korea There are various types of image tampering processes which have been considered in the multimedia forensic field. Among them, the resampling process is one of the most important issues. When several images are exquisitely spliced together, a resizing is typically applied. The resizing includes a resampling process as a core step. Therefore, it is possible to discriminate the image manipulation by detecting the fingerprint of the resampling process. Today, stereoscopic content is a rising keyword in the content market. Stereoscopic technology allows the viewer to experience a three-dimensional effect by displaying slightly different views to corresponding left and right eyes. Because new stereoscopic content is constantly being generated, the size of the stereoscopic market is growing exponentially. Despite the advantages of stereoscopic content, the stereoscopic technology has visual fatigue as a fundamental limitation. To overcome this limitation, a multiview technology has been developed. In the near future, multi-view content is expected to replace stereoscopic content. Also, the need for protection of the multi-view content is big. Since the device for generating multi-view content have a number of lens and the processor have high performance, the price for generating multi-view content is more expensive than the monoscopic one. Nevertheless, © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Choi et al. EURASIP Journal on Image and Video Processing (2017) 2017:22 forgery protection technology for multi-view content has rarely been developed. Multi-view content protection technology has advantages over the technology for monoscopic image in that it can use multiple images to detect forgery. But it is hard to realize the benefits without the consideration of the characteristics of multi-view content. If the existing resampling detection technique is repeatedly applied to the multi-view content without consideration of the characteristics of the multi-view content, only the unrelated results will be obtained. However, the method cannot utilize the relation among images in the multi-view content. Therefore, it is hard to expect sufficient improvement in detection performance. The multi-view image can be considered an extension of stereoscopic image. It means that the forensic work for stereoscopic images can naturally be extended to the multi-view content. Therefore, we conducted this study as a fundamental research for developing the ultimate protection technology for next generation multi-view content. In this paper, we propose an enhanced resampling detection algorithm for stereoscopic 3D images. In the proposed method, we apply a novel filtering method which separates the resampling detection process from the image’s own properties. The conspicuous regions filtering (CRF) process allows the detector to work well with low resampling factors and various types of image sets. Moreover, we developed a correlation-based stereo-signal synthesizing (CSS) scheme to properly use the relation of stereoscopic images as side information. This paper is organized as follows: in Section 2, we look into the previous resampling detection schemes and main contributions of this paper. In Section 3, we introduce the resampling process as well as the periodicity that exists in the resampled signal. In Section 4, we investigate the characteristics of forgery with stereoscopic images. In Section 5, we propose the resampling detection technique for 3D stereoscopic images, followed by the experimental results in Section 6. Finally, the Conclusion is drawn in Section 7. 2 Related work and main contributions 2.1 Related work Many resampling detection methods have been proposed in the past. Even though there are various ways to expose the resampling process, most techniques commonly use the relation between pixels. Studies related to resampling detection method using monoscopic image is as follows: Popescu and Farid developed a resampling process by analyzing invisible correlations from the resampled signals [1]. Using an expectation/maximization (EM) algorithm, th (...truncated)