Rotation Invariant Forgery Detection using LBP Variants
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2019 by IJETT Journal|
|Year of Publication : 2019|
|Authors : Ms. Gurpreet Kaur, Dr. Rajan Manro
|DOI : 10.14445/22315381/IJETT-V67I3P229|
MLA Style: Ms. Gurpreet Kaur, Dr. Rajan Manro "Rotation Invariant Forgery Detection using LBP Variants" International Journal of Engineering Trends and Technology 67.3 (2019): 152-157.
APA Style:Ms. Gurpreet Kaur, Dr. Rajan Manro (2019). Rotation Invariant Forgery Detection using LBP Variants. International Journal of Engineering Trends and Technology, 67(3), 152-157.
Digital Forensics is anoutlet of forensic science which is connected to cyber-crime. Mostly it includes the detection, recovery and investigation of digital devices. As we now in today’s world, Digital images and videos play most important role in digital forensics because they are the majorindicator of any crime scene. So the reliability of the image is important. These images can be easily manipulated and edited with the help of image processing tools. Under this, Copy-move Forgery is the most basic form of cyber-attack on digital images. In Copy-move forgery, particular amount of image (region) itself is copied and pasted into another fragmentof the same image. The idea behind this type of attack is to “add” or “delete” some objects from the image to break the faithfulness of the image and befool the viewer. This type of attack is more dominant in images having same texture or patterns, for e.g. sand, grass, water etc. In some cases when the copied region is processed before pasted i.e. some geometric transformations like rotation, scaling is applied on the pasted region. In such cases, It is not possible for human eyes to detect such kind of forgeries. When forgery is done in this way then techniques like block matching, key points are also unable to detect forgery. Soin thispaper, we explore some rotation invariant methods which are able to detect these kind of forgeries which include geometric transformations
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