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Inactive Method of Noncausal 2D Image Splice Recognition Model using Markov Model

Thofa Aysha1 , Manjesh R2

Section:Review Paper, Product Type: Conference Paper
Volume-04 , Issue-03 , Page no. 91-96, May-2016

Online published on Jun 07, 2016

Copyright © Thofa Aysha, Manjesh R . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Thofa Aysha, Manjesh R, “Inactive Method of Noncausal 2D Image Splice Recognition Model using Markov Model,” International Journal of Computer Sciences and Engineering, Vol.04, Issue.03, pp.91-96, 2016.

MLA Style Citation: Thofa Aysha, Manjesh R "Inactive Method of Noncausal 2D Image Splice Recognition Model using Markov Model." International Journal of Computer Sciences and Engineering 04.03 (2016): 91-96.

APA Style Citation: Thofa Aysha, Manjesh R, (2016). Inactive Method of Noncausal 2D Image Splice Recognition Model using Markov Model. International Journal of Computer Sciences and Engineering, 04(03), 91-96.

BibTex Style Citation:
@article{Aysha_2016,
author = { Thofa Aysha, Manjesh R},
title = {Inactive Method of Noncausal 2D Image Splice Recognition Model using Markov Model},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2016},
volume = {04},
Issue = {03},
month = {5},
year = {2016},
issn = {2347-2693},
pages = {91-96},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=71},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=71
TI - Inactive Method of Noncausal 2D Image Splice Recognition Model using Markov Model
T2 - International Journal of Computer Sciences and Engineering
AU - Thofa Aysha, Manjesh R
PY - 2016
DA - 2016/06/07
PB - IJCSE, Indore, INDIA
SP - 91-96
IS - 03
VL - 04
SN - 2347-2693
ER -

           

Abstract

Noncausal Markov model for a 2D signal is one of the inactive methods for spliced image. Image splicing is an image copies or merge a portion of image to same images or different images. The way Noncausal Markov model differs from traditional Markov model is the proposed methodology models a image as a 2-D noncausal signal and captures and analyzes the underlying dependencies between the current node and its neighbors in all directions. These dependencies are obtained through Discrete Cosine Transform and Discrete Wavelet Transform. These parameters give features to differentiate the natural ones with the features of spliced images. The noncausal Markov Model considers the input of block discrete cosine transformation domain, the discrete wavelet transform domain, and the cross-domain features for classification. The Expectation Maximization which is the classifier which classifies based on maximum likelihood of images. The dataset used is UCID dataset where we have uncompressed color images.

Key-Words / Index Term

Noncausal Markov Model, Discrete Cosine Transformation (DCT), Discrete Wavelet Transform(DWT), inactive image splicing recognition, Expectation Maximization(EM).

References

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