0341899 20240103193406.520100413235959.9 6 s. CD cav_un_epca*0341898978-1-4244-5498-31550-5790279-284PiscatawayIEEE2009 cyclostationarity image processing image forgery image forensics cav_un_auth*0101189 Saic Stanislav Zpracování obrazové informace Department of Image Processing ZOI ZOI UTIA-B Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0206076 Mahdian Babak Zpracování obrazové informace Department of Image Processing ZOI ZOI UTIA-B Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2010/ZOI/saic-a%20cyclostationarity%20analysis%20applied%20to%20image%20forensics.pdf GA102/08/0470 GA ČR cav_un_auth*0239565 CEZ:AV0Z10750506 The processing history of images plays an important role in many fields of digital image processing and computer vision. In this paper, we focus on geometrical transformations and show that images that have undergone such transformations contain hidden cyclostationary features. This makes possible employing the well–developed theory and efficient methods of cyclostationarity for blind analyzing of history of images in respect to geometrical transformations. To verify this, we also propose a cyclostationarity detection method and show how the traces of geometrical transformations in an image can be detected and the specific parameters of the transformation estimated. The method is based on the fact that a cyclostationary signal has a frequency spectrum correlated with a shifted version of itself. cav_un_auth*0261413 2009 IEEE Workshop on Applications of Computer Vision (WACV 2009) SnowBird Utah 07.12. 2009-09.12.2009 US 2011 IN http://hdl.handle.net/11104/0184749 2009 cav_un_epca*0341898 Proceedings of IEEE Workshop on Applications of Computer Vision (WACV 2009). 978-1-4244-5498-3 1550-5790 279 284 Piscataway IEEE 2009