TY - GEN
T1 - Digital forensics for printed source identification
AU - Tsai, Min-Jen
AU - Liu, Jung
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - Digital forensics
KW - Discrete Wavelet Transform (DWT)
KW - Graylevel co-occurrence Matrix (GLCM)
KW - Support Vector Machines (SVM)
UR - http://www.scopus.com/inward/record.url?scp=84883408516&partnerID=8YFLogxK
U2 - 10.1109/ISCAS.2013.6572349
DO - 10.1109/ISCAS.2013.6572349
M3 - Conference contribution
AN - SCOPUS:84883408516
SN - 9781467357609
T3 - Proceedings - IEEE International Symposium on Circuits and Systems
SP - 2347
EP - 2350
BT - 2013 IEEE International Symposium on Circuits and Systems, ISCAS 2013
T2 - 2013 IEEE International Symposium on Circuits and Systems, ISCAS 2013
Y2 - 19 May 2013 through 23 May 2013
ER -