Akademik Veri Yönetim Sistemi
29th Signal Processing and Communications Applications Conference (SIU 2021), Türkiye, 09 Haziran 2021, ss.1-4
In recent years, with the increase in the quantitative and content of signal processing data in the field of health, the workload of experts working in the field of radiology is accumulating daily. In addition to the complication of determining the correct diagnosis based on the images, there is the issue of probable violations of biomedical images and altering the images. Among these counterfeits on biomedical images, the most common forgery is copy-move. This forgery refers to the copying and transferring a part of the same image to another part. In this study, to the best of our knowledge, for the first time, a block-based copy-move forgery detection method was proposed using Local Similarity Pattern (LSP) texture extraction on a current biomedical data set.