Abstract: Systems and methods are provided through which a graphic image is classified in terms of being natural versus computer generated, or being a scientific slide presentation versus a comic image. The image is classified by extracting appropriate feature(s) from the image, and using the feature(s) to determine, within a predetermined degree of accuracy, the graphic classification of the image. The classification determination uses a trained model. The trained model is created by using machine learning algorithms such as Neural Networks, Support Vector Machines, and Learning Vector Quantizations. Subsequently, the trained model is used to classify a group of images of unknown classification automatically.

Abstract: Systems and methods are provided through which a graphic image is classified in terms of being natural versus computer generated, or being a scientific slide presentation versus a comic image. The image is classified by extracting appropriate feature(s) from the image, and using the feature(s) to determine, within a predetermined degree of accuracy, the graphic classification of the image.