Paper Contents
Abstract
With the widespread use of digital imaging technologies, image manipulation has become increasingly accessible, raising concerns about the authenticity and integrity of visual content. Digital image forensics aims to analyze and verify the credibility of images by detecting tampering, identifying sources, and retrieving hidden or altered information. This paper presents a comprehensive forensic process for digital images, encompassing stages such as acquisition, preprocessing, feature extraction, and authentication. Various forensic techniques, including metadata examination, error level analysis (ELA), and copy-move forgery detection, are explored to uncover inconsistencies. The integration of machine learning models further enhances the accuracy of forgery detection. The objective is to support legal and investigative processes by providing reliable tools for image verification. This work contributes to strengthening digital evidence standards and promoting trustworthy use of visual media in critical domain
Copyright
Copyright © 2025 TSKS.Jyothirmayi. This is an open access article distributed under the Creative Commons Attribution License.
