Stroke number and order free handwriting recognition for Nepali

Authors:
K. C. Santosh;Cholwich Nattee
Affiliations:
School of Information and Computer Technology, Sirindhorn International Institute of Technology, Thammasat University, PathumThani, Thailand;School of Information and Computer Technology, Sirindhorn International Institute of Technology, Thammasat University, PathumThani, Thailand
Venue:
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Year:
2006

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Abstract

This paper utilizes structural properties of those alphanumeric characters, which have variable writing units. Writing units reveal number, shape, size, order of stroke, and speed in writing. It uses a string of pen tip's positions and tangent angles of every consecutive point as a feature vector sequence of a stroke. We constructed a prototype recognizer that uses the "Dynamic Time Warping" (DTW) algorithm to align handwritten strokes with stored stroke templates and determine their similarity. Separate system is trained for original and preprocessed writing samples and achieved recognition rates of 85.87% and 88.59% respectively. This introduces novel real time handwriting recognition on Nepalese alphanumeric characters, which are independent of number of strokes, as well as their order.