The Research on Computer Recognition Technology for Blurred Alphabet Images

Abstract

This paper mainly studies the recognition issue of blurred alphabet images. If alphabets in an image is blurred, it is difficult t be recognized. To avoid the defect, the paper proposes a computer recognition method for blurred alphabet images based on grayscale class variance algorithm. The algorithm executes non-linear transformation on feature parameters of alphabets images extracted to obtain eigenvector coefficient weights, and then calculates characteristic correlation coefficient through wavelet transform to realize the blurred alphabet recognition. Experiments show that, the proposed method improves the accuracy of the blurred alphabets recognition and achieves satisfactory results.