  Direction properties of online strokes are used to analyze them in terms of
homogeneous regions or sub-strokes with points satisfying common geometric
properties. Such sub-strokes are called sub-units. These properties are used to
extract sub-units from Hindi ideal online characters. These properties along
with some heuristics are used to extract sub-units from Hindi online
handwritten characters.\\ A method is developed to extract point stroke,
clockwise curve stroke, counter-clockwise curve stroke and loop stroke segments
as sub-units from Hindi online handwritten characters. These extracted
sub-units are close in structure to the sub-units of the corresponding Hindi
online ideal characters.\\ Importance of local representation of online
handwritten characters in terms of sub-units is assessed by training a
classifier with sub-unit level local and character level global features
extracted from characters for character recognition. The classifier has the
recognition accuracy of 93.5\% on the testing set. This accuracy is the highest
when compared with that of the classifiers trained only with global features
extracted from characters in the same training set and evaluated on the same
testing set.\\ Sub-unit extraction algorithm and the sub-unit based character
classifier are tested on Hindi online handwritten character dataset. This
dataset consists of samples from 96 different characters. There are 12832 and
2821 samples in the training and testing sets, respectively.
