Evaluation and improvement of slant estimation for handwritten words

Handwritten words are usually slanted or italicized due to the mechanism of handwriting and one´s personality. The authors have proposed a chain code method for slant estimation and correction to improve the accuracy of character segmentation and recognition. However, the method is very simple and usually gives a good estimate of the word slant but the relationship between the actual slant and the estimated slant is nonlinear, and the slant tends to be underestimated when the absolute of the slant is close or greater than 45°. To resolve this, the paper proposes new methods for evaluating and improving the linearity and accuracy of slant estimation. The result of experimental study shows that the proposed algorithms are improved in the linearity and the accuracy of the slant estimation, and that a high speed iterative method is also efficient as far as processing time is concerned