Title :
CT-Scanner identification based on sensor noise analysis
Author :
Kharboutly, Anas ; Puech, William ; Subsol, Gerard ; Hoa, Denis
Author_Institution :
LIRMM, Univ. Montpellier 2, Montpellier, France
Abstract :
Medical image processing is considered as an important topic in the domain of image processing. It is used to help the doctors to improve and speed up the diagnosis process. In particular, computed tomography scanners (CT-Scanner) are used to create cross-sectional medical 3D images of bones. In this paper, we propose a method for CT-Scanner identification based on the sensor noise analysis. We built the reference noise pattern for each CT-Scanner from its 3D image, then we correlated the tested 3D images with each reference noise pattern in order to identify the corresponding CT-Scanner. We used a wavelet-based Wiener filter approach to extract the noise. Experimental results were applied on eight 3D images of 100 slices from different CT-Scanners, and we were able to identify each CT-Scanner separately.
Keywords :
Wiener filters; bone; computerised tomography; feature extraction; image denoising; medical image processing; wavelet transforms; CT-scanner identification; bones; computed tomography scanners; cross-sectional medical 3D images; diagnosis process; medical image processing; noise extraction; reference noise pattern; sensor noise analysis; wavelet-based Wiener filter approach; Biomedical imaging; Correlation; Forensics; Noise; Noise reduction; Three-dimensional displays; Wavelet transforms; Digital forensics; Wiener filter; authentication; denoise filtering; device identification; medical image forensics; noise pattern; sensor noise; wavelet transformation;
Conference_Titel :
Visual Information Processing (EUVIP), 2014 5th European Workshop on
Conference_Location :
Paris
DOI :
10.1109/EUVIP.2014.7018385