Investigation and Morphing Attack Detection Techniques in Multimedia: A Detail Review

Abstract

Multimedia forensics is an emerging field that focuses on the analysis of digital media to identify and authenticate digital evidence. It is a rapidly growing field that is being used in a variety of applications, including law enforcement, intelligence gathering, and digital forensics. This paper provides an overview of the current state of multimedia forensics and examines the various techniques used to detect and analyze digital evidence. This work examines the challenges associated with the use of these techniques and provides an overview of the current research in the field. Multimedia forensics involves the analysis of digital media to identify and authenticate digital evidence. This includes the analysis of images, audio, video, and other digital media. In addition to being widely used in special effects for entertainment, it is also used in computer vision and digital media. In this article, we investigated various morphing detection methods, techniques, and approaches in multimedia, i.e., image and video. Examinations of the number of "critical sites" are to be identified for successful morph detection as well as potential issues are included in the detailed description of the algorithms employed. Despite being one of the oldest methods, the mesh warping method is highly efficient. Facial recognition systems are susceptible to various biometric assaults because modern picture modification is now possible due to advancements in technology. In this study, the latest morphing attack detection techniques (MADT) approaches are compared and analyzed. On a variety of source picture databases, the effectiveness of various MADT methodologies is also contrasted. This work lists the limitations, benefits, and drawbacks of each morphing approach as well as how to generate morph images. Results are examined and contrasted with an in-depth analysis that sheds light on the weaknesses of current systems. The information presented in this paper is crucial for creating an advanced morphing attack detection scheme.