5743ecfa193f9a14009-26ec 20241225073505517 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Innovative Technology and Exploring Engineering IJITEE 22783075 10.35940/ijitee https://www.ijitee.org/ 12 30 2024 14 1 Department of ECE, Bhagwant University, Ajmer (Rajasthan), India. Mahesh Enumula https://orcid.org/0009-0009-5931-3830 Dr. M. Giri Department of CSE, Siddharth Institute of Engineering and Technology, Puttur (Karnataka), India. Dr. V. K. Sharma Department of ECE, Bhagwant University, Ajmer (Rajasthan), India. Image forgery detection has become increasingly critical with the proliferation of image editing tools capable of generating realistic forgeries. Traditional deep learning approaches, such as convolutional neural networks (CNNs), often struggle with capturing global dependencies and subtle inconsistencies across larger image contexts. To address these challenges, this paper proposes a novel Vision Transformer(ViT)- based framework for robust image forgery detection and localization. Leveraging the self-attention mechanism of transformers, our approach effectively models long-range dependencies and detects even subtle tampered regions with high precision. The proposed framework processes images as patch embeddings, extracting both local and global features, and outputs a detailed forgery map for accurate localization. We evaluate our method on multiple benchmark datasets containing diverse forgery types, including splicing, cloning, and inpainting. Experimental results demonstrate that the Vit based model outperforms state-of-the-art CNN and GAN-based methods, achieving superior accuracy, precision, and recall. Additionally, qualitative analyses highlight its capability to localize forgeries in complex scenarios. The results underscore the potential of Vision Transformers as a powerful tool for advancing the field of image forgery detection. 12 30 2024 12 30 2024 20 29 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true International Journal of Innovative Technology and Exploring Engineering (IJITEE) Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) Based on my understanding, this article has no conflicts of interest. This article has not been funded by any organizations or agencies. This independence ensures that the research is conducted with objectivity and without any external influence. The content of this article does not necessitate ethical approval or consent to participate with supporting documentation. The adequate resources of this article are publicly accessible. The authorship of this article is contributed equally to all participating individuals. 10.35940/ijitee.L1012.14011224 https://www.ijitee.org/portfolio-item/L101214011224/