Slant correction of handwritten strings based on structural properties of Korean characters

A slant correction method for handwritten Korean strings based on analysis of stroke distribution, which reflects structural properties of Korean characters, is presented in this paper. The method aims to deal with typical problems which have been frequently observed in slant correction of handwritten Korean strings with conventional approaches developed for English/European languages. Extracted strokes from a line of text image are classified into two clusters: vertical and diagonal. Gaussian modeling is applied to each of the clusters and the slant angle is estimated from the model which represents the vertical strokes. Experimental results support the effectiveness of the proposed method. For the performance comparison 1,600 handwritten address sting images were used, and success rate of 96.7%, which is much higher than other conventional approaches, has been achieved.