Normalization and rectification method for online hindi digit recognition with partial alignment algorithm

Research in data entry using light pen and other devices has always been of major interest over the past two decades. This is very helpful especially to those who are unable to use the keyboard fast enough. In this work, a new normalization and rectification method has been used, along with partial sequence alignment algorithm for online digit recognition. The normalization and rectification method was applied to obtain a unique sharp digit structure. A hybrid partial local-global sequence alignment is used to obtain the best matched digit DNA from the database as a two stage recognition process. The proposed method used stored data base samples for comparison purposes and then tested on 18 persons of different range in age with various writing styles. The normalization and rectification method was compared to smoothing method to determine the algorithm performance. The algorithm achieved 98.68% recognition accuracy when subjected with a normalization factor and thresholds adjusted to fixed values.