Size and orientation normalization of on-line handwriting using Hough transform

We introduce a new method for size and orientation normalization of unconstrained handwritten words based on the Hough transform. A modified Hough transform is applied to extremum points along the y coordinate to extract parallel lines corresponding to the boundary lines separating different vertical zones of the handwritten word. One dimensional Gaussian smoothing with variable variance is applied in the Hough space to alleviate the problems caused by the large variation in natural handwriting and the sparseness of extremum points. The method has been tested with and incorporated into an HMM based writer-independent, unconstrained on-line handwriting recognition system and a 25% error rate reduction has been achieved.