Pixel and Edge Based Illuminant Color Estimation for Image Forgery Detection

Abstract Images are one of the powerful media for communication. Image security is a main issue in the fields that using digital images. By the development of high resolution cameras, personal computers and photo-editing software's, the manipulation of images is becoming common. This paper mainly focuses on common form of image manipulation such as image splicing. The process of analysis is done with the help of inconsistencies in illuminant color of images. Illumination inconsistencies detection is a powerful way for image forgery detection. Inconsistency detection among different images can be identified with the help of pixel and edge based illuminant color estimation on image regions. From these illuminant estimators, extract shape and color features, which is then provided to a classifier for making decision. Classification using SVM and its performance is evaluated using distinct testing process. The main contribution of this method is, how illuminant color estimation on various constraints can be exploited as a forgery detection method and how these are provided for decision-making with minimal user interaction.

[1]  Hany Farid,et al.  Exposing Digital Forgeries Through Specular Highlights on the Eye , 2007, Information Hiding.

[2]  Zhang Xiong,et al.  3D lighting-based image forgery detection using shape-from-shading , 2012, 2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO).

[3]  Joost van de Weijer,et al.  Computational Color Constancy: Survey and Experiments , 2011, IEEE Transactions on Image Processing.

[4]  智一 吉田,et al.  Efficient Graph-Based Image Segmentationを用いた圃場図自動作成手法の検討 , 2014 .

[5]  Christian Riess,et al.  Scene Illumination as an Indicator of Image Manipulation , 2010, Information Hiding.

[6]  Joost van de Weijer,et al.  Improving Color Constancy by Photometric Edge Weighting , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  P.K. Bora,et al.  Illuminant colour based image forensics , 2008, TENCON 2008 - 2008 IEEE Region 10 Conference.

[8]  Hany Farid,et al.  Exposing Digital Forgeries in Complex Lighting Environments , 2007, IEEE Transactions on Information Forensics and Security.

[9]  H. Farid,et al.  Image forgery detection , 2009, IEEE Signal Processing Magazine.

[10]  Xuemin Wu,et al.  Image Splicing Detection Using Illuminant Color Inconsistency , 2011, 2011 Third International Conference on Multimedia Information Networking and Security.

[11]  Brian V. Funt,et al.  A comparison of computational color constancy Algorithms. II. Experiments with image data , 2002, IEEE Trans. Image Process..

[12]  Joost van de Weijer,et al.  Author Manuscript, Published in "ieee Transactions on Image Processing Edge-based Color Constancy , 2022 .

[13]  Jau-Ling Shih,et al.  Color Image Retrieval Based on Primitives of Color Moments , 2002, VISUAL.

[14]  Yingda Lv,et al.  An improved image blind identification based on inconsistency in light source direction , 2011, The Journal of Supercomputing.