Open Access

ARTICLE

Efficient Forgery Detection Approaches for Digital Color Images

Amira Baumy¹, Abeer D. Algarni^2,*, Mahmoud Abdalla³, Walid El-Shafai^4,5, Fathi E. Abd El-Samie^3,4, Naglaa F. Soliman^2,3

1 Department of Communications, High Institute for Engineering and Technology, Al-Obour Obour City, Egypt
2 Department of Information Technology, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia
3 Department of Electronics and Communications Engineering, Faculty of Engineering, Zagazig University, Zagazig, Sharqia, 44519, Egypt
4 Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menoufia, 32952, Egypt
5 Security Engineering Lab, Computer Science Department, Prince Sultan University, Riyadh, 11586, Saudi Arabia

* Corresponding Author: Abeer D. Algarni. Email:

Computers, Materials & Continua 2022, 71(2), 3257-3276. https://doi.org/10.32604/cmc.2022.021047

Received 21 June 2021; Accepted 08 September 2021; Issue published 07 December 2021

Abstract

This paper is concerned with a vital topic in image processing: color image forgery detection. The development of computing capabilities has led to a breakthrough in hacking and forgery attacks on signal, image, and data communicated over networks. Hence, there is an urgent need for developing efficient image forgery detection algorithms. Two main types of forgery are considered in this paper: splicing and copy-move. Splicing is performed by inserting a part of an image into another image. On the other hand, copy-move forgery is performed by copying a part of the image into another position in the same image. The proposed approach for splicing detection is based on the assumption that illumination between the original and tampered images is different. To detect the difference between the original and tampered images, the homomorphic transform separates the illumination component from the reflectance component. The illumination histogram derivative is used for detecting the difference in illumination, and hence forgery detection is accomplished. Prior to performing the forgery detection process, some pre-processing techniques, including histogram equalization, histogram matching, high-pass filtering, homomorphic enhancement, and single image super-resolution, are introduced to reinforce the details and changes between the original and embedded sections. The proposed approach for copy-move forgery detection is performed with the Speeded Up Robust Features (SURF) algorithm, which extracts feature points and feature vectors. Searching for the copied partition is accomplished through matching with Euclidian distance and hierarchical clustering. In addition, some pre-processing methods are used with the SURF algorithm, such as histogram equalization and single-mage super-resolution. Simulation results proved the feasibility and the robustness of the pre-processing step in homomorphic detection and SURF detection algorithms for splicing and copy-move forgery detection, respectively.

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Keywords

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