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Image Forgery is a very common problem faced in the multimedia world. People used to tamper the original images either to hide facts or to change the interpretation of the scene. There are many instances in history to support the statement. The toughest type of forgery detection is blind forgery detection. There is no clue available about the camera, author or location to corroborate the facts presented by the picture. Copy move forgery is one of the widely used forgeries in digital images. The people doing forgery make the task of forgery detection more difficult by using some post-processing operations like scaling rotation compression or changing lightning conditions like brightness, contrast, etc. The book presents a set of techniques to detect a forgery in the presence of post-processing operation of change of lighting conditions. The techniques use DCT, PCA transforms and their combinations to make the feature vectors robust to lightning conditions and time-efficient. The techniques have been presented in a way to help new researchers looking to work in the area. A thorough analysis has been done using popular image data sets.
About the author
Sunil Kumar est un historien de renom, connu pour sa connaissance approfondie des civilisations anciennes et des transformations culturelles. Grâce à ses nombreuses publications acclamées et à ses recherches approfondies, il éclaire le passé et le relie au présent. Éducateur passionné, il incite ses élèves à aimer l'histoire.
