06-06-2017, 02:38 PM
In recent years, due to advances in network technologies, low-cost multimedia devices, sophisticated image and video editing software, and broad adoptions of digital multimedia encoding standards, digital multimedia applications have become increasingly popular in our daily life. However, the digital nature of media files can now be easily manipulated, synthesized and manipulated in many ways without leaving visible clues. As a result, the integrity of the image / video content can no longer be taken for granted and a number of issues related to forensic medicine arise. Two types of forensic schemas are widely used for the detection of image / video forgeries: active schemas and passive schemas. With active schemes, the altered region can be extracted using a pre-embedded watermark. However, this schema must have source files to embed the watermark first; Otherwise, the detection process will fail. In contrast, passive schemes extract some intrinsic image / video fingerprints to detect altered regions.
The technological advancement of several video and image processing tools has made digital video tuning easy and fast. This review article focuses on the passive techniques used to detect forgeries in a digital video. Passive counterfeit detection techniques are methods used to detect the authenticity of a video without relying on pre-built information. The techniques exploit the use of statistical or mathematical properties that are distorted as a result of video tampering for counterfeit detection. The passive video counterfeit detection approach has a broad perspective on multimedia security, information security and pattern recognition. In this work, we divided passive techniques for video forensics into three categories; Statistical correlation of video characteristics, frame-based to detect statistical anomalies, and inconsistency characteristics of different digital equipment. The discussion also covers trends, limitations and the idea for improvements in passive counterfeit detection techniques.
The technological advancement of several video and image processing tools has made digital video tuning easy and fast. This review article focuses on the passive techniques used to detect forgeries in a digital video. Passive counterfeit detection techniques are methods used to detect the authenticity of a video without relying on pre-built information. The techniques exploit the use of statistical or mathematical properties that are distorted as a result of video tampering for counterfeit detection. The passive video counterfeit detection approach has a broad perspective on multimedia security, information security and pattern recognition. In this work, we divided passive techniques for video forensics into three categories; Statistical correlation of video characteristics, frame-based to detect statistical anomalies, and inconsistency characteristics of different digital equipment. The discussion also covers trends, limitations and the idea for improvements in passive counterfeit detection techniques.