Detection of Copy Move Forgery Using a Hybrid Algorithm

Image forgery detection in terms of copy-move detection has become a hot topic among scholars in recent years. This paper provides a system that combines saliency detection and local binary pattern-based forgery detection for real-time images. Saliency detection is used in the preliminary phase to identify the forged component. To certify the integrity of the original image, this forgery detection approach can be used in medical, forensics, and media. It connects the modified portion’s territory to the surrounding (global) area, securing the modified portion’s territory. Local Binary Pattern characteristics are then used to detect or capture the specific pixels/regions for the tampered portions. This hybrid approach retains the advantages of both the saliency map and the Local Binary Pattern, particularly in terms of scaling and rotation, while also having a higher detection rate than existing methods. The proposed method, in addition to the existing forgery detection result, leverages depth map information to correctly identify the faked region. Bits per pixel are used to determine the severity of the modified section. The proposed technology is unusual in that it can detect altered areas of digital photos in real time. In a state-of-the-art comparison, the proposed method is proven to be significantly superior than existing methods.

Author (S) Details

Tekuru Chandra Sekhar Rao
Sri Venkateswara Engineering College, Tirupati, India.

Sateesh Kumar Kanagala
Sreenidhi Institute of Science and Technology, Hyderabad, India.

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