Open AccessA generalized ghost detection and segmentation method for double-joint photographic experts group compression
Author(s) -
Sepideh Azarianpour,
Amir Sadri
Publication year - 2019
Publication title -
journal of medical signals and sensors
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.337
H-Index - 21
ISSN - 2228-7477
DOI - 10.4103/jmss.jmss_19_19
Subject(s) - computer science , jpeg , segmentation , artificial intelligence , computer vision , grayscale , image segmentation , digital image , median filter , image processing , pattern recognition (psychology) , image (mathematics)
The versatility of digital photographs and vast usage of image processing tools have made the image manipulation accessible and ubiquitous. Thus, there is an urgent need to develop digital image forensics tools, specifically for joint photographic experts group (JPEG) format which is the most prevailing format for storing digital photographs. Existing double JPEG methods needs improvement to reduce their sensitivity to the random grid shifts which is highly common in manipulation scenario. Also, a fully automatic pipeline, in terms of segmentation followed by the classifier is still required.