In today's internet world, all the data are represented and stored in digital form. Almost any entity in this world can be represented digitally, ranging from simple text to complex multimedia work. Now, the challenge is to claim the ownership and prevent theft of one's own digital data. Multimedia theft has driven the attention of many stakeholders who spend huge money and precious time in creating or making such valuable digital data. Among all the multimedia entities, image files are more vulnerable for theft since it is the basic component of any visuals. The notion of this research work is to propose an image theft detection model which will determine whether partial theft or complete theft of an image has occurred or not. A biometric feature, i.e., fingerprint of the owner is embedded on the digital image at a micro level, such that even a very small portion of image theft can be determined, and the ownership of the image can be claimed by the owner. This research is limited to the spatial domain, i.e. raw image. Assessment metrics of the results shows that embedding the biometric feature on an image does not distort the image quality and its artifacts.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.