An Improved Nonlinear Normalization Method and Its Application to Handwritten Legal Amount Recognition on Chinese Cheque

An improved nonlinear normalization method based on density equalization of the exact character area is proposed for recognition of unconstrained handwritten Chinese characters on an image of Chinese cheque. By the method, the density of strokes, calculated based on the thickness of the stroke and the space between strokes, can minimize the localization and irregularity of the shape distortions of the characters. Strokes in different characters are also normalized to have the equal thickness. By modifying the expression of density equalization according to the exact character area, the problems of global incline and highlighting of certain strokes are effectually rectified. Experiments show that the nonlinear normalization method can get better shape correction effect than other methods. Application of this method to handwritten legal amount recognition to Chinese cheques showed the rate of correct recognition is improved by around 1.5%.