Proceeding of

National Conference

on

Recent Trends in Mobile

and Cloud Computing

(NCRMC-2014)

17-18 December, 2014

 

as

A Special Issue of

International Journal of Computer Science and Applications

(ISSN:0974-1011)

Chief Patron

Shri Banwarilal Purohit 

Chairman,RCOEM

 

Shri Govindlal Agarwal

General Secretary, RCOEM

 

Patron

 

 Prof. Q.H.Jeevaji

Director, DMT, RCOEM

 

Dr. R.S. Pande

Principal,RCOEM

A

 

Conveners

Dr. M. B. Chandak

(Head, Dept. of CSE)

 

Co-convener

Dr. A. J. Agrawal

 

Organizing Committee

Prof. M. R. Wanjari

Prof. S. G. Mundhada

Prof. A.V. Buche

Prof. N. N. Tirpude

Prof. K. P. Khurana

Prof. D. A. Borikar

Prof. A. R. Raipurkar

Organized by

Description: RCOEM_Logo.png

Dept of Computer Science & Engineering,

Shri Ramdeobaba College of Engineering and Management, Nagpur – 440013.

Website: www.rknec.edu

 

In association with

Description: logo.dept.science.gif

Department of Science & Technology

 

 

Editor

K. H. Walse

M.S.India

 

 

 

   
   
   
   
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
  
IJCSA ISSN: 0974-1011 (Online) >>    
Title:

Illumination Color Classification Based Image Forgery Detection: A Review 
Author:
 Nitish L.  Nirmalkar and Shailesh D. Kamble
 
Abstract

Over the years, photographs have been used as document of events as well as proof in legal proceedings. Although some of photographers are able to manipulate the images and make composites of original images, this process requires expert knowledge and demands lot of time. In today’s world, a lot of skillfully developed image editing softwares are available which makes image manipulation and modifications an easy task. This reduces trust in photographs and presents an open question on authenticity of images and photographs. This paper, aims at focusing on the most common forms of image manipulation, which is called as image splicing. Here we propose a forgery detection method which uses inconsistencies in illumination of images. For achieving this, we make use of physics and statistics based illuminant estimators. These illuminant estimates are used to extract features which are then given to a machine-learning technique which supports us in decision-making.

©2015 International Journal of Computer Science and Applications 

Published by Research Publications, India