Source and Target Region Discrimination on Copy-Move Image Forgery Using SegFormer Model

Imam Ekowicaksono; Rinaldi Munir; Masayu Leylia Khodra

doi:10.1109/ISRITI64779.2024.10963403

Source and Target Region Discrimination on Copy-Move Image Forgery Using SegFormer Model

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Imam Ekowicaksono, Rinaldi Munir, Masayu Leylia Khodra

2024 7th International Seminar on Research of Information Technology and Intelligent Systems: Advanced Intelligent Systems in Contemporary Society, ISRITI 2024 - Proceedings Conference paper Cited by 0

Abstract

Copy-move image forgery is a type of image manipulation where a part of an image is copied and pasted onto another part of the same image. Detecting copy-move image forgery involves identifying duplicated region and discriminating between the source and target regions, which can provide investigators with insights into the purpose of the forgery. This research aims to discriminate between the source and target regions in copy-move image forgery using SegFormer. SegFormer is a transformer-based semantic segmentation model. This research train SegFormer architecture from scratch to differentiate source and target regions. Experiments on the CoMoFoD dataset show that the SegFormer model achieved a mIoU score over 60%, demonstrating its effectiveness in discriminating source and target regions on a publicly available dataset. © 2024 IEEE.

Affiliations

Institut Teknologi Bandung, Sekolah Teknik Elektro dan Informatika, Bandung, Indonesia; Institut Teknologi Sumatera, Teknik Informatika, FTI, South Lampung, Indonesia

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