%0 Journal Article %1 Bashir2009 %A IEEE, %B CIB: 2009 IEEE WORKSHOP ON COMPUTATIONAL INTELLIGENCE IN BIOMETRICS: THEORY, ALGORITHMS, AND APPLICATIONS %C 345 E 47TH ST, NEW YORK, NY 10017 USA %D 2009 %I IEEE %K biometricpersonauthentication biometricPINrecognition multidimensionaltimeseries biometricsmartpenBiSP biometricsignatureverification dynamictimewarpingDTW %P 63--68 %T Person Authentication with RDTW based on Handwritten PIN and Signature with a Novel Biometric Smart Pen Device %X This paper presents writer authentication using features of handwritten single characters, PIN words and signatures. The kinematics and dynamics of handwriting movement were recorded with a novel ballpoint pen equipped with a diversity of sensors mounted inside the pen. The time series provided by five different sensor channels including refill and finger grip pressures, acceleration and tilt data was analyzed by using a DTW algorithm. To speed up computation a ``Reduced Dynamic Time Warping RDTW'' technique was applied which is based on the sum of sensor channels and a two steps down-sampling of the multi-dimensional time series. Preliminary results have shown that processing time and memory size could significantly be reduced without deterioration of authentication performance using single characters, signatures and PIN words. Excellent accuracy in recognition was achieved which is mainly due to RDTW technique and the high quality of data sampled by a novel pen device. %@ 978-1-4244-2773-4

@article{Bashir2009, abstract = {{This paper presents writer authentication using features of handwritten single characters, PIN words and signatures. The kinematics and dynamics of handwriting movement were recorded with a novel ballpoint pen equipped with a diversity of sensors mounted inside the pen. The time series provided by five different sensor channels including refill and finger grip pressures, acceleration and tilt data was analyzed by using a DTW algorithm. To speed up computation a ``Reduced Dynamic Time Warping RDTW{''} technique was applied which is based on the sum of sensor channels and a two steps down-sampling of the multi-dimensional time series. Preliminary results have shown that processing time and memory size could significantly be reduced without deterioration of authentication performance using single characters, signatures and PIN words. Excellent accuracy in recognition was achieved which is mainly due to RDTW technique and the high quality of data sampled by a novel pen device.}}, added-at = {2011-01-17T13:09:32.000+0100}, address = {{345 E 47TH ST, NEW YORK, NY 10017 USA}}, affiliation = {Bashir, M (Reprint Author), Univ Appl Sci Regensburg, Fac Elect \& Informat Technol, Regensburg, Germany. [}, author = {IEEE}, biburl = {https://www.bibsonomy.org/bibtex/28920073e91f06b24290ae8c289ef457d/hkayabilisim}, booktitle = {{CIB: 2009 IEEE WORKSHOP ON COMPUTATIONAL INTELLIGENCE IN BIOMETRICS: THEORY, ALGORITHMS, AND APPLICATIONS}}, cited = {0}, file = {:home/hkaya/Projeler/diagnus/Screener/doc/literature/Bashir2009.pdf:PDF}, id = {ISI:000271116700010}, interhash = {41e570478ba546718f535d344266518e}, intrahash = {8920073e91f06b24290ae8c289ef457d}, isbn = {978-1-4244-2773-4}, keywords = {biometricpersonauthentication biometricPINrecognition multidimensionaltimeseries biometricsmartpenBiSP biometricsignatureverification dynamictimewarpingDTW}, language = {English}, note = {{IEEE Workshop on Computational Intelligence in Biometrics - Theory, Algorithms and Applications, Nashville, TN, MAR 30-APR 02, 2009}}, organization = {{IEEE}}, pages = {{63--68}}, publisher = {{IEEE}}, references = {9}, timestamp = {2011-01-17T13:09:32.000+0100}, title = {{Person Authentication with RDTW based on Handwritten PIN and Signature with a Novel Biometric Smart Pen Device}}, type = {{Proceedings Paper}}, year = {{2009}} }