A Novel Approach for Detection of Alteration in Ball Pen Writings

Addition or alteration to documents that have profound implication is very common. The technique that Forensic Document Examiners (FDEs) use for the examination of such documents is basically a physical examination. In this paper we consider the alteration detection as a two-class pattern recognition problem. Image processing techniques are used for feature extraction and a neural network based feature analysis technique is used for finding a set of discriminatory features. The results using a nearest neighbor classifier are very encouraging. The results also demonstrate the effectiveness of feature analysis.