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http://dx.doi.org/10.13089/JKIISC.2021.31.6.1171

Forgery Detection Scheme Using Enhanced Markov Model and LBP Texture Operator in Low Quality Images  

Agarwal, Saurabh (Amity University)
Jung, Ki-Hyun (Kyungil University)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.31, no.6, 2021 , pp. 1171-1179 More about this Journal
Abstract
Image forensic is performed to check image limpidness. In this paper, a robust scheme is discussed to detect median filtering in low quality images. Detection of median filtering assists in overall image forensic. Improved spatial statistical features are extracted from the image to classify pristine and median filtered images. Image array data is rescaled to enhance the spatial statistical information. Features are extracted using Markov model on enhanced spatial statistics. Multiple difference arrays are considered in different directions for robust feature set. Further, texture operator features are combined to increase the detection accuracy and SVM binary classifier is applied to train the classification model. Experimental results are promising for images of low quality JPEG compression.
Keywords
Forgery detection; Texture operator; Median filtering;
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