Online Handwritten Feature with Proportional Invariant

B. Kruatrachue, K. Siriboon, W. Chatwiriya, and K. Bounnady (Thailand)


handwritten feature, chain code, handwritten recognition


This paper proposed high level feature for online handwritten recognition. This feature must be high level enough so that the feature is not change when characters are written by different persons at different speed and different proportion (shorter or longer stroke, head, tail, loop, curve). In this high level feature, a character is divided in to sequence of curve segments where a segment start where curve change rotation (counter clockwise and clockwise). In each segment, following features are gathered cumulative change in direction of curve (- for clockwise), cumulative curve length, cumulative length of left to right, right to left, top to bottom and bottom to top ( cumulative change in X and Y axis of segment). This feature is simple yet robust for high accuracy recognition. The feature can be gather from parsing the original time sampling sequence X, Y point of the pen location without re-sampling. Experiments results show that the recognition rates are at 90.5 %.

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