Rotated Kanji Character Recognition

We proposed a rotated character recognition method using eigen-subspace characterized multiple projection and simple projection. Then the multiple projections showed a higher accuracy at low dimensions than a simple projection for alphanumeric 62 categories. This time, we applied it for the first class of Japanese Industrial Standard (JIS) Kanji set which includes 2,965 categories. As the result, very high recognition accuracy over 99.8% was achieved especially by the multiple projections of the input rotated images