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.
Highlights
Security of the image content in the modern multimedia system is an issue of the primary concern of researchers in the last decade
The most common algorithms are splicing algorithms and copy-move algorithms. These algorithms depend on different approaches such as Discrete Wavelet Transform (DWT), Local Binary Pattern (LBP), and Scale Invariant Feature Transform (SIFT)
The Histogram equalization (HE) and Single Image Super-Resolution (SISR) are applied as pre-processing techniques to improve the images before extracting the Speeded Up Robust Features (SURF) key points to improve the copy-move forgery detection
Summary
Security of the image content in the modern multimedia system is an issue of the primary concern of researchers in the last decade. Security of image content can be accomplished through several strategies such as watermarking, encryption, steganography, and image forgery detection. The recent forgery detection algorithms [5,6,7,8] can be classified according to the types of image forgery. The most common algorithms are splicing algorithms and copy-move algorithms. The main contribution of the paper is to apply the pre-processing techniques on the images before extracting the features and develop robust forgery detection methods for splicing and copy-move forgery attacks based on simple signal processing tools.
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