A Relaxation Algorithm That Uses Word Collocation to Improve Text Recognition Performance

A method is presented for postprocessing the output of a word recognition algorithm for visual text recognition. A word recognition algorithm typically outputs a list of alternatives for the identity of each word in a running text. Each alternative is ranked by the probability that it is correct. A relaxation algorithm is proposed in this paper that re-ranks the alternatives for each word using word collocation statistics. These are measurements of the probability that two words occur nearby each other in a running text. The improvement in performance is measured by the increase in the percentage of correct alternatives in the first position. Experimental results are presented that show the proposed algorithm can improve the performance of a word recognition algorithm from 56% to over 83% correct in the top position of the candidate lists. Keywords: text recognition, word recognition, postprocessing, OCR, word collocation, probabilistic relaxation, results propagation. 0 revised versi..