A Image Forensics Analysis by Using DST, Fuzzy and Bayesian Approaches
作者： G.Selvavinayagam , D.Gokila Bharathi
DOI:
关键词: Data mining 、 Image (mathematics) 、 Focus (optics) 、 Hash function 、 Bayesian probability 、 Computer science 、 Fuzzy logic 、 Probabilistic logic
摘要: A Forensic Image is often accompanied by a calculated Hash signature to validate that the image an exact duplicate of original. It mainly focus on detection artifacts introduced single processing tool. Hence making it necessary for developing several artifacts. In this paper we introduce different theoretical frameworks, based Dempster-Shafer’s Theory Evidence, Fuzzy and Bayesian decision fusion respectively, perform heterogeneous, incomplete or conflicting outputs forensic algorithms. These models are easily expandable arbitrary number tools, do not require tools output be probabilistic take into account available information about reliability. To proposed approaches, carried out some experiments addressing simple yet realistic scenario in which three exploit double JPEG compression detect cut paste tampering within specified region image. The results obtained encouraging, especially when compared with performance method binary OR operator.
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