Recognizing Characters with Severe Perspective Distortion Using Hash Tables and Perspective Invariants

In this paper, we present a novel method to recognize characters with severe perspective distortion using hash tables and perspective invariants. The proposed algorithm consists of storage and voting stages. With the help of perspective invariants, the combinations of 4-tuple bases for the perspective invariant coordinate system are searched out in an efficiently way. The bases are further selected so that the resulting transformation is effective. The characters´ features under the perspective invariant coordinate system determine an entry in a one dimensional hash table, which is applied for storage and retrieval. Experimental results show the superior performance of the proposed method in comparison to other existing methods.