Author(s): Kavita V.Hulmukhe | S.S.Sane | Alpana A. Borse
Journal: International Journal of Computer Applications
ISSN 0975-8887
Volume: iccia;
Issue: 3;
Date: 2012;
Original page
Keywords: DWT | geometric operations (flip and rotation) | KPCA | PCA | region duplications
ABSTRACT
With the advancement of technology and easy availability of imaging tools, it's not difficult now days to manipulate digital images to hide or create misleading images. Image forgery detection is currently one of the hot research fields of image processing. A duplication detection approach that can adopt two robust features based on discrete wavelet transform (DWT) and principal component analysis (PCA).Extension of PCA is KPCA techniques detect 'Flip' and 'Rotation' types of forgeries. Proposed technique that extends the basic algorithm for detecting 'Scaling' types of forgeries. This method uses global geometric transformation and the labeling technique to indentify the mentioned forgeries. Experiments with a good number of natural images show very promising results, when compared with the conventional PCA-based approach.
Journal: International Journal of Computer Applications
ISSN 0975-8887
Volume: iccia;
Issue: 3;
Date: 2012;
Original page
Keywords: DWT | geometric operations (flip and rotation) | KPCA | PCA | region duplications
ABSTRACT
With the advancement of technology and easy availability of imaging tools, it's not difficult now days to manipulate digital images to hide or create misleading images. Image forgery detection is currently one of the hot research fields of image processing. A duplication detection approach that can adopt two robust features based on discrete wavelet transform (DWT) and principal component analysis (PCA).Extension of PCA is KPCA techniques detect 'Flip' and 'Rotation' types of forgeries. Proposed technique that extends the basic algorithm for detecting 'Scaling' types of forgeries. This method uses global geometric transformation and the labeling technique to indentify the mentioned forgeries. Experiments with a good number of natural images show very promising results, when compared with the conventional PCA-based approach.
