Digital Forensics for Printed Source Identification

Abstract

Recently, digital forensics, which involves the collection and analysis of the origin digital device, has become an important issue. Digital content can play a crucial role in identifying the source device, such as serve as evidence in court. To achieve this goal, we use different texture feature extraction methods such as gray-level co-occurrence matrix (GLCM) and discrete wavelet transform (DWT), to analyze the Chinese printed source in order to find the source of printers. Furthermore, we also explore the optimum feature subset by using feature selection techniques and using support vector machine (SVM) to identify the source model of the documents. The average experimental results attain a 98.64% identification rate which is significantly superior to the existing known method by 1.2%. This higher testing performance demonstrates that the proposed identification method is very useful for source laser printer identification.