NDLI: The application of intelligent system to digital image forensics

Content Provider	IEEE Xplore Digital Library
Author	Cheng-Liang Lai Yi-Shiang Chen
Copyright Year	2009
Description	Author affiliation: Department of Informatics, Fo Guang University, R.O.C. (Cheng-Liang Lai; Yi-Shiang Chen)
Abstract	Digital image capture devices, such as digital cameras or camera-equipped mobile phones, have become very common. Digital images also have the problem of being easy to edit and to tamper. As a result, digital forensics is now an important field in image processing. In this study, the features of images taken different cameras were used as the basis for determining the source of the digital images. The Genetic Algorithm was used to automatically select the most suitable and minimum number of features for the image content then the Support Vector Machine used for training and classification in order to identify the source cameras. This study also used image editing software for the post-processing of images, including resizing, blurring and tamper in order to determine if the Genetic Algorithm selected features were still effective for identification after the images were tampered. The results showed that the features selected automatically using the Genetic Algorithm could not only use less features, but also achieved better identification rates for the source camera of the digital images, and save images to extract the time of features after Genetic Algorithm select optimal feature.
Starting Page	2991
Ending Page	2998
File Size	315442
Page Count	8
File Format	PDF
ISBN	9781424437023
DOI	10.1109/ICMLC.2009.5212589
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-07-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent systems Digital images Forensics Digital cameras Genetic algorithms Watermarking Charge-coupled image sensors Machine learning Cybernetics Mobile handsets Feature selection Image source identification Genetic algorithm Support vector machine Feature extraction
Content Type	Text
Resource Type	Article

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