RECOGNITION AND SEGMENTATION OF CONNECTED CHARACTERS WITH SELECTIVE ATTENTION

We have modified the original model of selective attention, which was previously proposed by Fukushima, and extended its ability to recognize and segment connected characters in cursive handwriting. Although the original model of selective attention already had the ability to recognize and segment patterns, it did not always work well when too many patterns were presented simultaneously. In order to restrict the number of patterns to be processed simultaneously, a search controller has been added to the original model. The new model mainly processes the patterns contained in a small ''search area,'' which is moved by the search controller A preliminary experiment with computer simulation has shown that this approach is promising. The recognition and segmentation of characters can be successful even though each character in a handwritten word changes its shape by the effect of the characters before and behind.