Improving noise immunity of "sliding" correlation algorithm for printable characters recognition - Кушниренко, Олег Анатольевич; Cадченко Андрей Валерьевич; Троянский, Александр Вячеславович (Eastern-European Journal of Enterprise Technologies, 2014)
Solving the problem of character information recognition is relevant in the analysis of text documents, identification of the character information on printed circuit boards and electronic components, recognition of labels on containers and railway cars, etc. Optimal matching algorithm, which provides the highest probability of a correct distinction, lies in calculating the correlation coefficient between the recognizable character and a set of all templates. A simple noise-immune algorithm for character information recognition that does not use the procedure of pre-segmentation and contour filtering, based on the combination of the correlation method and the minimum code distance criterion was proposed in the paper. The proposed algorithm allows significantly improve the probability of correct character recognition by slight complication of the processing algorithm and allows to determine the coordinates of characters, corresponding to one given pattern for one iteration. The obvious advantage of this algorithm is the absence of multiplication operations. Herewith, the computational complexity of the algorithm is reduced due to the lack of multiplication operations and decrease in the total number of addition operations.