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http://dx.doi.org/10.5573/ieie.2015.52.1.061

Median Filtering Detection using Latent Growth Modeling  

Rhee, Kang Hyeon (Chosun University, College of Electronics and Information Eng., Dept. of Electronics Eng.)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.52, no.1, 2015 , pp. 61-68 More about this Journal
Abstract
In recent times, the median filtering (MF) detector as a forensic tool for the recovery of forgery images' processing history has concerned broad interest. For the classification of MF image, MF detector should be designed with smaller feature set and higher detection ratio. This paper presents a novel method for the detection of MF in altered images. It is transformed from BMP to several kinds of MF image by the median window size. The difference distribution values are computed according to the window sizes and then the values construct the feature set same as the MF window size. For the MF detector, the feature set transformed to the model specification which is computed using latent growth modeling (LGM). Through experiments, the test image is classified by the discriminant into two classes: the true positive (TP) and the false negative (FN). It confirms that the proposed algorithm is to be outstanding performance when the minimum distance average is 0.119 in the confusion of TP and FN for the effectivity of classification.
Keywords
Median filter; Median filtering detector; Digital image forensics; Latent growth modeling (LGM); Structural equation modeling (SEM);
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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