EXPLOITING NOISE AND TEXTURAL FEATURES FOR PASSIVE IMAGE FORENSICS

Surbhi Gupta, Neeraj Mohan, Parvinder Singh Sandhu

Abstract


Advancement in information technology and image processing has resulted in image tampering and its forensics. This paper aims at detecting image manipulations by exploiting the various noise and texture characteristics of the image. Various filters and edge detectors are used to capture the noise and texture characterizes of the image. Statistical features such as mean and variance are extracted and then utilized for differentiating original image from manipulated one. SVM classifier is used for classifying images as authentic or forged. Experiments proved that proposed integrated technique performs much better than existing state of art techniques.

Keywords


Image tampering, noise discrepancies, feature extraction, textural information, quality metrics, statistical evaluation

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References


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DOI: https://doi.org/10.26483/ijarcs.v8i8.3397

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