Character recognition apparatus

Abstract

This invention enables easy and fast selection of candidates for an inputted character image among the character categories by search of a tree-structured dictionary. Each ordinary node of the tree structure has three branches, that is two ordinary nodes and one reject node, and compares the multivalued feature extracted from the inputted character image for the node concerned, with a threshold, upper limit and lower limit values. If the feature value is out of the limited range, the search goes down to the reject node at the next level. If not, the search goes down to the right or left node at the next level based on the comparison of the feature value with the threshold value. Reject nodes have no branch. The tree structure has character category information as leaves connected to the bottom ordinary nodes and another character category information for all the reject nodes. Search of the dictionary gives character category information indicating the candidates, which are thereafter tested by detailed matching for outputting recognition results. In particular, this invention can use white pel run length as multivalued features. The white pel run length is defined as the run length of white pels from a point on an edge of the segmentation window to the nearest black pel or edge in a direction. It is easy to construct and optimize the dictionary, since many varieties of white run length are generated from little sampling data.