Florida International University
Edit Your Profile
FIU Discovery
Toggle navigation
Browse
Home
People
Organizations
Scholarly & Creative Works
Research Facilities
Support
Edit Your Profile
Identification of smartphone-image source and manipulation
Conference
Liu, Q, Li, X, Chen, L
et al
. (2012). Identification of smartphone-image source and manipulation .
EURO-PAR 2011 PARALLEL PROCESSING, PT 1,
7345 LNAI 262-271. 10.1007/978-3-642-31087-4_28
Share this citation
Twitter
Email
Liu, Q, Li, X, Chen, L
et al
. (2012). Identification of smartphone-image source and manipulation .
EURO-PAR 2011 PARALLEL PROCESSING, PT 1,
7345 LNAI 262-271. 10.1007/978-3-642-31087-4_28
Copy Citation
Share
Overview
Identifiers
Additional Document Info
View All
Overview
cited authors
Liu, Q; Li, X; Chen, L; Cho, H; Cooper, PA; Chen, Z; Qiao, M; Sung, AH
authors
Chen, Zhongxue
abstract
As smartphones are being widely used in daily lives, the images captured by smartphones become ubiquitous and may be used for legal purposes. Accordingly, the authentication of smartphone images and the identification of post-capture manipulation are of significant interest in digital forensics. In this paper, we propose a method to determine the smartphone camera source of a particular image and operations that may have been performed on that image. We first take images using different smartphones and purposely manipulate the images, including different combinations of double JPEG compression, cropping, and rescaling. Then, we extract the marginal density in low frequency coordinates and neighboring joint density features on intra-block and inter-block as features. Finally, we employ a support vector machine to identify the smartphone source as well as to reveal the operations. Experimental results show that our method is very promising for identifying both smartphone source and manipulations. Our study also indicates that applying unsupervised clustering and supervised classification together (clustering first, followed by classification) leads to improvement in identifying smartphone sources and manipulations and thus provides a means to address the complexity issue of intentional manipulation. © 2012 Springer-Verlag.
publication date
August 1, 2012
published in
DISTRIBUTED COMPUTING (DISC 2014)
Book
Identifiers
Digital Object Identifier (DOI)
https://doi.org/10.1007/978-3-642-31087-4_28
Additional Document Info
start page
262
end page
271
volume
7345 LNAI