Abstract
Fingerprinting of digital images is the process of finding evidence from the tampered images by the use of image’s metadata and machine learning algorithm. In the recent decades, digital images growing tremendously in the people’s life, and digital images have been used in many application areas. Hereafter, digital image integrity should not be taken for granted because now a days popular powerful software used for image editing are available in the Internet at low cost. Because of the technological evolution and the availability of powerful image editing software, digital crimes also increase tremendously. To identify the legitimacy of the image files, we propose a new methodology for the digital image forgery detection by combining the analysis of metadata’s exchangeable image file format (Exif) information, statistical features and also with the help of error level analysis method (ELA) that can help the forensic investigators to authenticate the digital image files by distinguishing the difference between the real image and the fake image.
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