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Image Registration based on Support Vector Machine for Tampering Localization
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 85 - Number 7 |
| Year of Publication: 2014 |
| Authors: Jyoti Rao, Sheetal Kusal, Swati Nikam, Archana Chougule |
10.5120/14853-3219
|
Jyoti Rao, Sheetal Kusal, Swati Nikam, Archana Chougule . Image Registration based on Support Vector Machine for Tampering Localization. International Journal of Computer Applications. 85, 7 ( January 2014), 23-26. DOI=10.5120/14853-3219
Abstract
Different technologies are available on web. In the era of internet communication, systems should able to protect content such as pictures, videos against malicious modifications during their transmission. One of the important problems addressed in this is the authentication of the image received in a Communication. Tampering detection has significance in authentication of image. This paper presents support vector machine (SVM) based tampering detection system. In this a robust alignment (registration) method is proposed which makes use of an image hash component based on the Bag of Features (BOF) paradigm to localize the tampering. These BOF are clustered for effective image alignment. The support vector machine is optimal partitioning based linear classifier and at least theoretically better other classifier because only small numbers of classes required during classification SVM. The proposed signature is attached to the image before transmission and then analyzed at destination to recover the geometric transformations which have been applied to the received image. A block-wise tampering detection which uses histograms of oriented gradients (HOG) presentation is proposed. The proposed approach obtains better margin in providing an overall enhanced performance by reducing the training time while maintaining the accuracy.
References
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