An empirical cross-validation of denoising filters for PRNU extraction. (November 2018)

• Record Type: Journal Article
• Authors: Gupta, Bhupendra; Tiwari, Mayank
• Is Part Of: Forensic science international. Volume 292(2018)
• Page Start: 110
• Page End: 114
• Publication Date: 2018-11
• Subjects: Photo Response Non-Uniformity -- Digital image forensics -- Source camera identification -- Source camera verification; Medical jurisprudence -- Periodicals; Chemistry, Forensic -- Periodicals; Forensic Medicine -- Periodicals; Médecine légale -- Périodiques; Chimie légale -- Périodiques; Gerechtelijke geneeskunde; Gerechtelijke chemie; Gerechtelijke psychiatrie; Chemistry, Forensic; Medical jurisprudence; Electronic journals; Periodicals; Electronic journals; 614.1
• DOI: 10.1016/j.forsciint.2018.09.017
• Languages: English
• ISSNs: 0379-0738

Abstract

Graphical abstract: Highlights: The work is an empirical study to check theimportance of widely used PRNU extraction de-noising filters. Theimportance is checked at different stages of source camera identification procedure. The proposed work is unique in the sense that it gives an idea about: ○ best de-noising filter. ○ best value of noise variance for PRNU extraction. ○ best method of camera-PRNU enhancement. ○ dominant part (query-image/camera-PRNU) in SCI work. This work empirically shows that camera-PRNU enhancement methods are dependent on de-noising filter. Abstract: The present work is an empirical study to check the importance of widely used PRNU extraction de-noising filters at different stages of source camera identification procedure. The proposed work is unique in the sense that it gives an idea about the choice of the appropriate de-noising filters at the time of PRNU extraction for formation of unique identification pattern of digital camera and noise residue extraction of query image. Also in this work, we have suggested the best values of σ (noise variance) for formation of unique identification pattern of digital camera and noise residue extraction of query image (based on empirical observations). This study has been performed to check that which part (camera unique identification pattern, noise residue, enhancement methods, and value of σ ) mostly dominates the performance of source camera identification.