Abstract—On-line handwritten character recognition system
is a special line of research in image processing and pattern
recognition field, it can also considered a special process of in
academic researches and production fields in the past decade.
The general steps in a recognition system are pre-processing,
segmentation, feature extraction and classifications. The
techniques of pre-processing stage play an excessive role in the
system and directly affect the system performance. The focus of
this article is on doing pre-processing stage and providing a
most desirable data set form the raw data using in feature
extraction and then to increase the rate of recognition system.
For this reason, the novel algorithm is presented for finding a
critical points set of hand-drawn letters. These critical points
help extracting the correct structural and statistical features of
on-line character handwriting in any given style writing.
Index Terms—Persian and Arabic script, critical points, on-line character recognition, pre-processing.
Majid Harouni is with UTMViCube Lab, Faculty of Computer Science and Information Systems, Universiti Technologi Malaysia, Johor, Malaysia and with the Department of Computer Science, Islamic Azad University, Dolatabad branch, Isfahan, Iran (e-mail: majid.harouni@ gmail.com).
Dzulkifli Mohamad and Mohd Shafry Mohd Rahim are with the UTMViCube Lab, Faculty of Computer Science and Information Systems, Universiti Technologi Malaysia, Johor, Malaysia (e-mail: email@example.com, and firstname.lastname@example.org).
Sami M. Halawani is with the Faculty of Computing and Information Technology, King Abdul Aziz University, Saudi Arabia (e-mail: email@example.com).
Cite:Majid Harouni, Dzulkifli Mohamad, Mohd Shafry Mohd Rahim, and Sami M. Halawani, "Finding Critical Points of Handwritten Persian/Arabic Character," International Journal of Machine Learning and Computing vol.2, no. 5, pp. 573-577, 2012.