Ing. Babak Mahdian, Ph.D.
research fellow

Department:
Department of Image Processing
Research interests:
All aspects of image processing, computer vision, and AI, with a particular focus on image and video retrieval, forensics, and low-data regime detection and recognition.
Biography
Publication list
Babak received the M.Sc. degree in computer science from the West Bohemia University, Plzen, Czech Rebpublic and the Ph.D. degree from the Czech Technical University, Prague, Czech Republic, in 2008. From 2008 to 2010, he was on a postdoctoral position in the Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic. He has been awarded by the city of New York (New York Next Idea 2011), České hlava 2011 (category called “Industrie”), and Otto Wichterle award (an honour given by the Czech Academy of Sciences).
Curriculum-Vitae: here
Journal articles
- Extended IMD2020: a large‐scale annotated dataset tailored for detecting manipulated images, IET Biometrics 10 4 (2021), p. 392-407 Download Download DOI: 10.1049/bme2.12025 [2021] :
- PIZZARO: Forensic analysis and restoration of image and video data, Forensic Science International 264 1 (2016), p. 153-166 Download DOI: 10.1016/j.forsciint.2016.04.027 [2016] :
- Detecting Cyclostationarity in Re-Captured LCD Screens, Journal of Forensic Research 6 4 (2015) Download DOI: 10.4172/2157-7145.1000294 [2015] :
- Blind Verification of Digital Image Originality: A Statistical Approach, IEEE Transactions on Information Forensics and Security 8 9 (2013), p. 1531-1540 Download DOI: 10.1109/TIFS.2013.2276000 [2013] :
- Efficient image duplicated region detection model using sequential block clustering, Digital Investigation 10 1 (2013), p. 73-84 Download DOI: 10.1016/j.diin.2013.02.007 [2013] :
- A bibliography on blind methods for identifying image forgery, Signal Processing-Image Communication 25 6 (2010), p. 389-399 Download DOI: 10.1016/j.image.2010.05.003 [2010] :
- Blind Methods for Detecting Image Fakery, IEEE Aerospace and Electronic Systems Magazine 25 4 (2010), p. 18-24 Download DOI: 10.1109/MAES.2010.5467652 [2010] :
- Using noise inconsistencies for blind image forensics, Image and Vision Computing 27 10 (2009), p. 1497-1503 Download DOI: 10.1016/j.imavis.2009.02.001 [2009] :
- Blind Authentication Using Periodic Properties ofInterpolation, IEEE Transactions on Information Forensics and Security 3 3 (2008), p. 529-538 DOI: 10.1109/TIFS.2004.924603 [2008] :
- Detection of copy–move forgery using a method based on blur moment invariants, Forensic Science International 171, p. 180-189 [2007] :
Other publications
- IMD2020: A Large-Scale Annotated Dataset Tailored for Detecting Manipulated Images, 2020 IEEE Winter Applications of Computer Vision Workshops (WACVW), p. 71-80 Download DOI: 10.1109/WACVW50321.2020.9096940 [2020] :
- Imaging device identification and detection of image tampering, Abstract book of 7th European Academy of Forensic Science Conference Download [2015] :
- Identification of Aliasing-Based Patterns in Re-Captured LCD Screens, Proceedings of the 2015 IEEE International Conference on Image Processing, ICIP 2015, p. 616-620 Download DOI: 10.1109/ICIP.2015.7350872 [2015] :
- Determination of Stop-Criterion for Incremental Methods Constructing Camera Sensor Fingerprint, Digital-Forensics and Watermarking, p. 47-59 Download DOI: 10.1007/978-3-319-19321-2_4 [2015] :
- PIZZARO - Prostředky pro identifikaci obrazového záznamového zařízení, autentifikaci a rekonstrukci obrazu (2014) Download [2014] :
- A Novel Method for Identifying Exact Sensor Using Multiplicative Noise Component, Proceedings of the IEEE International Symposium on Multimedia (ISM), 2013, p. 241-247 Download DOI: 10.1109/ISM.2013.46 [2013] :
- Identifying image forgeries using change points detection, Media Watermarking, Security, and Forensics III Download DOI: 10.1117/12.872510 [2011] :
- Image Tampering Detection Using Methods Based on JPEG Compression Artifacts: A Real-Life Experiment, Proceedings of ISABEL'11 Download DOI: 10.1145/2093698.2093874 [2011] :
- JPEG Quantization Tables Forensics: A Statistical Approach, Computational Forensics : Proceedings of the 4th International Workshop, IWCF 2010, p. 150-159, Eds: Sako Hiroshi, Franke Katrin Y., Saitoh Shuji Download DOI: 10.1007/978-3-642-19376-7_13 [2011] :
- Detecting Double Compressed JPEG Images, Proceedings of the 3rd International Conference on Imaging for Crime Detection and Prevention 2009 (ICDP 2009) Download [2010] :
- A Cyclostationarity Analysis Applied to Image Forensics, Proceedings of IEEE Workshop on Applications of Computer Vision (WACV 2009)., p. 279-284 Download [2009] :
- A Cyclostationarity Analysis Applied to Scaled Images, Neural Information Processing, p. 683-690, Eds: Leung C.S., Lee M., Chan J.H. Download [2009] :
- Detection and Description of Geometrically Transformed Digital Images, Media Forensics and Security (Proceedings of Spie), p. 1-9 Download [2009] :
- Blinds Methods for Detecting Image Fakery, Proceedings of 42nd Annual 2008 IEEE International Carnahan Conference on Security Technology, p. 280-286, Eds: Sanson L.D., Fliegel K. Download [2008] :
- Detection of Resampling Supplemented with Noise Inconsistencies Analysis for Image Forensics, Selected Papers of the Sixth International Conference on Computational Science and Applications, p. 546-556, Eds: Gavrilova Marina, Gervasi Osvaldo, Lagana Antonio, Mun Youngsong, Iglesias Andrés Download [2008] :
- Detection of Near-Duplicated Image Regions, Computer Recognition Systems 2, p. 187-195, Eds: Kurzynski Marek , Puchala Edward Download [2007] :
- Image Segmentation Based on Local Noise Variance, ÚTIA AV ČR (Praha, 2007) [2007] :
- On Periodic Properties of Interpolation and Their Application To Image Authentication, Proceedings of the Third International Symposium on Information Assurance and Security, p. 439-444 [2007] :
- Periodic Properties Of Resampled Images, ÚTIA AV ČR (Praha, 2007) [2007] :
- Hidden Periodicity in Interpolated Signals and in Their Derivatives, ÚTIA AV ČR (Praha, 2007) [2007] :
- A Moment-based Approach to Duplicated Image Regions Detection, ÚTIA AV ČR (Praha, 2006) [2006] :