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Image Forgery Detection using SIFT and PCA Classifiers for Panchromatic Images


Author(s):

Shivani Thakur , CGCTC, Jhanjeri, Mohali; Ramanpreet Kaur, CGCTC, Jhanjeri, Mohali; Jasmeet Kaur, CGCTC, Jhanjeri, Mohali

Keywords:

PCA, SIFT, PSNR

Abstract:

The image forgery is the technique in which pixels are marked in the image which are not similar to other pixels of the images. In the base paper technique of PCA is applied for the detection of image forgery. The PCA is the classification of neural networks which will analyze each pixel of the image and classify pixels according to pixel type. The PCA algorithm takes training and trained dataset as input and drive new values according to input image. In this work, improvement is proposed in PCA algorithm for image forgery and proposed improvement is based on SIFT algorithm. The SIFT algorithm is the algorithm which analyze each pixel of the image and define type of pixels in the image. The output of the SIFT algorithm is given as input to PCA algorithm for data classification. The PCA algorithm will classify the data according to SIFT algorithm output. The results show that proposed algorithm performs well in terms of PSNR, MSE, and fault detection rate and accuracy value.


Other Details:

Manuscript Id :IJSTEV3I1037
Published in :Volume : 3, Issue : 1
Publication Date: 01/08/2016
Page(s): 57-62
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