Title :
Blind source camera identification
Author :
Kharrazi, Mehdi ; Sencar, Husrev T. ; Memon, Nasir
Author_Institution :
Dept. of Electr. Eng. & Comput. Eng., Polytech. Univ. Brooklyn, NY, USA
Abstract :
An interesting problem in digital forensics is that given a digital image, would it be possible to identify the camera model which was used to obtain the image. In this paper we look at a simplified version of this problem by trying to distinguish between images captured by a limited number of camera models. We propose a number of features which could be used by a classifier to identify the source camera of an image in a blind manner. We also provide experimental results and show reasonable accuracy in distinguishing images from the two and five different camera models using the proposed features.
Keywords :
cameras; feature extraction; identification; image classification; image colour analysis; blind source camera identification; camera color characteristics; camera model identification; camera source identification; digital image forensics; feature extraction; image classification; image quality metrics; legal photographic evidence; Blood; Digital cameras; Digital forensics; Digital images; Image processing; Law enforcement; Layout; Legal factors; Manufacturing; Watermarking;
Conference_Titel :
Image Processing, 2004. ICIP '04. 2004 International Conference on
Conference_Location :
Singapore
Print_ISBN :
0-7803-8554-3
DOI :
10.1109/ICIP.2004.1418853