Journal Title : International Journal of Modern Trends in Engineering and Science

Author’s Name : Anju S Prasad | S Antony Mutharasan

Volume 02 Issue 09  Year 2015

ISSN no: 2348-3121  

Page no: 20-24

Abstract With the rapid development of digital media editing techniques, digital image manipulation becomes rather convenient and easy. With the increasing applications of digital imaging, different types of software tools are introduced for image processing. They are used to combine two images to make it look real or objects can be added or deleted. The manipulation techniques include deletion of details, insertion of details, combining multiple images and false captioning. Detecting these image manipulations has become an important problem. To avoid these problems SVM classifier is proposed which have similar functional form to neural networks. Image, texture and pixel value based features are extracted and analyzed from the images. Then hash values are calculated for these features.  The process consists of two phases which are training phase and a testing phase.  SVM classifier is trained with a set of images and used to classify the images as genuine or forged. SVM supports both regression and classification tasks and can handle multiple continuous and categorical variables. This method reduces the time and computational complexity.

Keywords— SVM, digital forensics, image forgery, contrast enhancement, composite Image


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