Abstrato

Detection of Digital Image Forgeries by Illuminant Color Estimation and Classification

S. Rajapriya, S. Nima Judith Vinmathi

Digital Image forgery is very common nowadays and is done without much difficulty with the help of powerful image editing software’s mainly to cover up the truthfulness of the photographs which often serve as evidence in courts. In this paper, we propose a forgery detection method to expose the photographic manipulations known as image composition or splicing by exploiting the color inconsistencies in the illuminated image. For this, effective illuminant estimators are used to obtain illuminant estimates of the image from which texture and edge based features are extracted. The features are used for automatic decision making and finally Extreme Learning machine (ELM) is applied to classify the forged image from the original one.