Advanced SearchSearch Tips
Camera Identification of DIBR-based Stereoscopic Image using Sensor Pattern Noise
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Camera Identification of DIBR-based Stereoscopic Image using Sensor Pattern Noise
Lee, Jun-Hee;
  PDF(new window)
Stereoscopic image generated by depth image-based rendering(DIBR) for surveillance robot and camera is appropriate in a low bandwidth network. The image is very important data for the decision-making of a commander and thus its integrity has to be guaranteed. One of the methods used to detect manipulation is to check if the stereoscopic image is taken from the original camera. Sensor pattern noise(SPN) used widely for camera identification cannot be directly applied to a stereoscopic image due to the stereo warping in DIBR. To solve this problem, we find out a shifted object in the stereoscopic image and relocate the object to its orignal location in the center image. Then the similarity between SPNs extracted from the stereoscopic image and the original camera is measured only for the object area. Thus we can determine the source of the camera that was used.
Stereoscopic Image;Depth Image-based Rendering;Sensor Pattern Noise;Camera Identification;
 Cited by
S. Sim and J. Min, "A Study on 3D Telepresence Image for Remote Control of Rescue Robot," 22th Ground System Development Conference, 2014.

C. Fehn, "Depth-Image-Based Rendering(DIBR), Compression and Transmission for a New Approach on 3D-TV," in Proc. SPIE Conf. Stereoscopic Displays and Virtual Reality Systems XI, pp. 93-104, 2004.

L. Wang, C. Hou, J. Lei and W. Yan, "View Generation with DIBR for 3D Display System," Multimedia Tools Appl, pp. 74:9529-9545, 2015. crossref(new window)

H. Kim, J. Lee, T. Oh and H. Lee, "Robust DT-CWT Watermarking for DIBR 3D Images," IEEE Trans. On Broadcasting, Vol. 58, No. 4, pp. 533-543, December 2012. crossref(new window)

Y. Lin and J. Wu, "A Digital Blind Watermarking for Depth-Image-Based Rendering 3D Images," IEEE Trans. on Broadcasting, Vol. 57, No. 2, pp. 602-611, June 2011. crossref(new window)

C. Choi and H. Lee, "Detection of the Single Image Leaked from DIBR System Based on the Horizontal Neighboring Pixels," International Conference on 3D Systems and Applications, Hsinchu, pp. 506-510, June 2012.

D. Jung and H. Lee, "Detection of the Single Image from DIBR Based on 3D Warping Trace and Edge Matching," Journal of Computer and Communications, Vol. 2, pp. 43-50, 2014.

H. Choi, D. Hyun and H. Lee, "Enhanced Resampling Detection for DIBR Stereoscopic Image," International Conference on 3D Systems and Applications, Hsinchu, pp. 506-510, June 2012.

K. Choi, E. Lam and K. Wang, "Sour Camera Identification using Footprints from Lens Aberration," Proc. of SPIE, 2006.

L. Van, S. Emmanuel and M. Kankanhalli, "Identifying Source Cell Phone using Chromatic Aberration," ICME, 2007.

S. Bayram, H. Sencar, N. Memon and I. Avcibas "Source Camera Identification based on CFA Interpolation," ICIP, Vol. 3, pp. III-69-72, 2005.

Z. Geradts, J. Bijhold, M. Kieft, K. Kurosawa, K. Kuroki and N. Saitoh, "Methods for Identification of Images Acquired with Digital Cameras," SPIE, Vol. 4243, pp. 505-512, 2001.

J. Lukas, J. Fridrichm and M. Goljan, "Digital Camera Identification from Sensor Pattern Noise," IEEE Trans Inf Forensics and Security, 1(2):205214, 2006.

H. Farid, "Digital Image Ballistics from JPEG Quantization," Dept. Comput. Sci., Dartmouth College, Tech. Rep. TR2006-583.

L. Zhang and W. Tam, "Stereoscopic Image Generation based on Depth Images for 3D TV," IEEE Trans. Broadcasting, Vol. 51, No. 2, pp. 191-199 June 2005. crossref(new window)

C. Vazquez, W. Tam and F. Speranza, "Stereoscopic Imaging: Filling Disoccluded Areas in Depth Image -Based Rendering," SPIE, 6392, 2006.

M. Bertalmio, G. Sapiro, V. Caselles and C. Ballester, "Image Inpainting. Proceedings of ACM SIGGRAPH," New Orleans, pp. 417-424, July 2000.

L. Po, S. Zhang, X. Xu and Y. Zhu, "A New Multidirectional Extrapolation Hole-Filling Method for Depth-Image-Based Rendering," 18th IEEE International Conference on Image Processing(ICIP), Brussels, pp. 2589-2592, September 2011.

D. De Silva, W. Fernando and H. Arachchi, "A New Mode Selection Technique for Coding Depth Maps of 3D Video," IEEE International Conference on Acoustics Speech and Signal Processing, pp. 686-689, March 2010.

J. Fridrich, "Digital Image Forensic using Sensor Noise," IEEE Signal Processing Magazine, 26(2): 2637, 2009.

M. Roushdy, "Comparative Study of Edge Detection Algorithms Applying on the Grayscale Noisy Image Using Morphological filter," International Journal of Graphics, Vision, and Image Processing GVIP, Vol. 6, Issue 4, pp. 17-23, Dec. 2006.

P. Soille, Morphological Image Analysis: Principles and Applications. Berlin, Germany: Spring-Verlag, 1999.

Kinect camera,

M. Goljan and J. Fridrich, "Camera Identification from Scaled and Cropped Images," Electronic Imaging, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, SPIE, pp. 68190E, 2008.