TY - JFULL AU - Khampheth Bounnady and Boontee Kruatrachue and Somkiat Wangsiripitak PY - 2007/6/ TI - On-line Lao Handwritten Recognition with Proportional Invariant Feature T2 - International Journal of Computer and Information Engineering SP - 1421 EP - 1425 VL - 1 SN - 1307-6892 UR - https://publications.waset.org/pdf/13414 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 5, 2007 N2 - This paper proposed high level feature for online Lao 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 reverse 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. We also experiment on other segmentation point such as the maximum curvature point which was widely used by other researcher. Experiments results show that the recognition rates are at 94.62% in comparing to using maximum curvature point 75.07%. This is due to a lot of variations of turning points in handwritten. ER -