Reduced Dynamic Time Warping for Handwriting Recognition Based on Multidimensional Time Series of a Novel Pen Device
The purpose of this paper is to present a Dynamic
Time Warping technique which reduces significantly the data
processing time and memory size of multi-dimensional time series
sampled by the biometric smart pen device BiSP. The acquisition
device is a novel ballpoint pen equipped with a diversity of sensors
for monitoring the kinematics and dynamics of handwriting
movement. The DTW algorithm has been applied for time series
analysis of five different sensor channels providing pressure,
acceleration and tilt data of the pen generated during handwriting on
a paper pad. But the standard DTW has processing time and memory
space problems which limit its practical use for online handwriting
recognition. To face with this problem the DTW has been applied to
the sum of the five sensor signals after an adequate down-sampling
of the data. Preliminary results have shown that processing time and
memory size could significantly be reduced without deterioration of
performance in single character and word recognition. Further
excellent accuracy in recognition was achieved which is mainly due
to the reduced dynamic time warping RDTW technique and a novel
pen device BiSP.
[1] http://www.bisp-regensburg.de
[2] C. Gruber, C. Hook, J. Kempf, G. Scharfenberg, B. Sick, " A Flexible
Architecture for Online Signature Verification Based on a Novel
Biometric Pen" In Proceedings of the 2006 IEEE Mountain Workshop
on Adaptive and Learning Systems (SMCals/06)"; pp. 110-115; Logan,
2006.
[3] T. Gruber, C. Gruber, B. Sick, " Online Signature Verification With new
Time Series Kernels for Support Vector Machines" D. Zhang, A. K.
Jain (Eds.) Advances in Biometrics: International Conference ICB 2006;
Lecture Notes in Computer Science 3832, Springer Verlag, Berlin,
Heidelberg, New York; pp. 500-508; Hong Kong, 2006
[4] Hook C., Kempf J., Scharfenberg, G."New Pen Device for Biometrical
3D Pressure Analysis of Handwritten Characters, Words and
Signatures." Proceedings ACM Multimedia Berkeley, USA (2003) 38-
44
[5] Hook C., Kempf J., Scharfenberg G, "A Novel Digitizing Pen for the
Analysis of Pen Pressure and Inclination in handwriting Biometrics",
Biometric Authentication Workshop, Prague 2004, Lecture Notice in
Computer Science. Springer 2004.
[6] Šoule M., Kempf J. "Handwritten Text Analysis through Sound. A New
Device for Handwriting Analysis", In Proceedings IWSSIP, Prague,
(2003) 254-257
[7] Šoule, M, "Person Authentification Using Acoustic Handwritten Text",
Ph.D. thesis, Pilsen (2007), Czech Republic.
[8] M. Dose, C. Gruber, A. Grunz, C. Hook, J. Kempf, G. Scharfenberg, B.
Sick, "Towards an Automated Analysis of Neuroleptics- Impact on
Human Hand Motor Skills", In Proceedings of the 2007 IEEE
Symposium on Computational Intelligence in Bioinformatics and
Computational Biology (CIBCB 2007)"; pp. 494-501, Honolulu, 2007
[9] A. Ünlü, R. Brause, K. Krakow," Handwriting Analysis for Diagnosis
and Prognosis of Parkinson-s Disease", Proc.Int. Symp. Biological and
Medical Data analysis, LNCS Vol. 4345,Springer Heidelberg
2006,pp.441-450
[10] TakitaT., Hangai S., Kempf J, Hook C., Scharfenberg G., "An
Identification of Japanese Numerical Characters on a Biometrical Smart
Pen System", In Automatic Identification Advanced Technologies, 2007
IEEE Workshop, June 2007.
[11] Tapperet C., Suen C., Wakahara T, "The State of the Art in On-line
Handwriting Recognition", IEEE Trans. Pattern Analysis and Machine
Intelligence, Vol.12, No.8, 1990, pp.787-808.
[12] R. Niels, L. Vuurpijl, "Dynamic Time Warping Applied to Tamil
Character Recognition". Proceedings of the 8th International Conference
on Document Analysis and Recognition, 2005.
[13] Marcos Faundez Zanuy, "On-line signature recognition based on VQDTW",
ELSEVIER, June, 2006.
[14] Kruskall, J.B., Liberman,M., "The Symmetric Time Warping Algorithm:
From continuous to discrete". In time Warps, String Edits and
Macromolecules: The Theory and Practice of Sequence Comparison,
pp.125-161,, Addison -Wesley (1983)
[15] Eamonn J. Keogh, Michael J. Pazzani, "Derivative Dynamic Time
Warping" In Proc. Of the 1st SIAM Int.Conf. on Data Mining (SDM-
2001).
[16] V. Vuori, J. Laaksonen, E. Oja, J. Kangas, "Speeding up On-line
Recognition of Handwritten Characters by Pruning the Prototype Set" In
Proc.Of (ICDAR-01), pp.501-505.
[17] Salvador S., Chan P.: "FastDTW: Toward Accurate Dynamic Time
Warping in Linear Time and Space", Intelligent Data Analysis, 2007.
[18] H. Sakoe, S. Chiba, "Dynamic programming algorithm optimization for
spoken word recognition". IEEE Transaction on Acoustics, Speech and
Signal Processing, Vol 26, NO1, pp. 43-49. February 1978.
[19] http://www.bromba.com/faq/biofaqe.htm#ROC
[20] www.mathworks.com
[1] http://www.bisp-regensburg.de
[2] C. Gruber, C. Hook, J. Kempf, G. Scharfenberg, B. Sick, " A Flexible
Architecture for Online Signature Verification Based on a Novel
Biometric Pen" In Proceedings of the 2006 IEEE Mountain Workshop
on Adaptive and Learning Systems (SMCals/06)"; pp. 110-115; Logan,
2006.
[3] T. Gruber, C. Gruber, B. Sick, " Online Signature Verification With new
Time Series Kernels for Support Vector Machines" D. Zhang, A. K.
Jain (Eds.) Advances in Biometrics: International Conference ICB 2006;
Lecture Notes in Computer Science 3832, Springer Verlag, Berlin,
Heidelberg, New York; pp. 500-508; Hong Kong, 2006
[4] Hook C., Kempf J., Scharfenberg, G."New Pen Device for Biometrical
3D Pressure Analysis of Handwritten Characters, Words and
Signatures." Proceedings ACM Multimedia Berkeley, USA (2003) 38-
44
[5] Hook C., Kempf J., Scharfenberg G, "A Novel Digitizing Pen for the
Analysis of Pen Pressure and Inclination in handwriting Biometrics",
Biometric Authentication Workshop, Prague 2004, Lecture Notice in
Computer Science. Springer 2004.
[6] Šoule M., Kempf J. "Handwritten Text Analysis through Sound. A New
Device for Handwriting Analysis", In Proceedings IWSSIP, Prague,
(2003) 254-257
[7] Šoule, M, "Person Authentification Using Acoustic Handwritten Text",
Ph.D. thesis, Pilsen (2007), Czech Republic.
[8] M. Dose, C. Gruber, A. Grunz, C. Hook, J. Kempf, G. Scharfenberg, B.
Sick, "Towards an Automated Analysis of Neuroleptics- Impact on
Human Hand Motor Skills", In Proceedings of the 2007 IEEE
Symposium on Computational Intelligence in Bioinformatics and
Computational Biology (CIBCB 2007)"; pp. 494-501, Honolulu, 2007
[9] A. Ünlü, R. Brause, K. Krakow," Handwriting Analysis for Diagnosis
and Prognosis of Parkinson-s Disease", Proc.Int. Symp. Biological and
Medical Data analysis, LNCS Vol. 4345,Springer Heidelberg
2006,pp.441-450
[10] TakitaT., Hangai S., Kempf J, Hook C., Scharfenberg G., "An
Identification of Japanese Numerical Characters on a Biometrical Smart
Pen System", In Automatic Identification Advanced Technologies, 2007
IEEE Workshop, June 2007.
[11] Tapperet C., Suen C., Wakahara T, "The State of the Art in On-line
Handwriting Recognition", IEEE Trans. Pattern Analysis and Machine
Intelligence, Vol.12, No.8, 1990, pp.787-808.
[12] R. Niels, L. Vuurpijl, "Dynamic Time Warping Applied to Tamil
Character Recognition". Proceedings of the 8th International Conference
on Document Analysis and Recognition, 2005.
[13] Marcos Faundez Zanuy, "On-line signature recognition based on VQDTW",
ELSEVIER, June, 2006.
[14] Kruskall, J.B., Liberman,M., "The Symmetric Time Warping Algorithm:
From continuous to discrete". In time Warps, String Edits and
Macromolecules: The Theory and Practice of Sequence Comparison,
pp.125-161,, Addison -Wesley (1983)
[15] Eamonn J. Keogh, Michael J. Pazzani, "Derivative Dynamic Time
Warping" In Proc. Of the 1st SIAM Int.Conf. on Data Mining (SDM-
2001).
[16] V. Vuori, J. Laaksonen, E. Oja, J. Kangas, "Speeding up On-line
Recognition of Handwritten Characters by Pruning the Prototype Set" In
Proc.Of (ICDAR-01), pp.501-505.
[17] Salvador S., Chan P.: "FastDTW: Toward Accurate Dynamic Time
Warping in Linear Time and Space", Intelligent Data Analysis, 2007.
[18] H. Sakoe, S. Chiba, "Dynamic programming algorithm optimization for
spoken word recognition". IEEE Transaction on Acoustics, Speech and
Signal Processing, Vol 26, NO1, pp. 43-49. February 1978.
[19] http://www.bromba.com/faq/biofaqe.htm#ROC
[20] www.mathworks.com
@article{"International Journal of Electrical, Electronic and Communication Sciences:62655", author = "Muzaffar Bashir and Jürgen Kempf", title = "Reduced Dynamic Time Warping for Handwriting Recognition Based on Multidimensional Time Series of a Novel Pen Device", abstract = "The purpose of this paper is to present a Dynamic
Time Warping technique which reduces significantly the data
processing time and memory size of multi-dimensional time series
sampled by the biometric smart pen device BiSP. The acquisition
device is a novel ballpoint pen equipped with a diversity of sensors
for monitoring the kinematics and dynamics of handwriting
movement. The DTW algorithm has been applied for time series
analysis of five different sensor channels providing pressure,
acceleration and tilt data of the pen generated during handwriting on
a paper pad. But the standard DTW has processing time and memory
space problems which limit its practical use for online handwriting
recognition. To face with this problem the DTW has been applied to
the sum of the five sensor signals after an adequate down-sampling
of the data. Preliminary results have shown that processing time and
memory size could significantly be reduced without deterioration of
performance in single character and word recognition. Further
excellent accuracy in recognition was achieved which is mainly due
to the reduced dynamic time warping RDTW technique and a novel
pen device BiSP.", keywords = "Biometric character recognition, biometric person
authentication, biometric smart pen BiSP, dynamic time warping
DTW, online-handwriting recognition, multidimensional time series.", volume = "2", number = "9", pages = "2044-7", }
