A robust method of recognizing multi-font rotated characters

This work presents a new robust recognition method for rotated character images. We first construct an eigen sub-space for each category using the covariance matrix calculated from a sufficient number of rotated patterns averaged by several fonts. Next, we can obtain a locus by projecting their rotated characters onto the eigen subspace and interpolating between their projected points. An unknown character is also projected onto the eigen sub-space of each category. Then, verification is carried out by calculating the distance between the projected point of the unknown character and the locus. In our experiment, we obtained quite good results for three fonts of 26 capital letters of the English alphabet.