Abstract
Natural scene images contain a variety of characters in different type of fonts. The camera and environmental factors could cause the characters to be deformed and be broken. The deformable and broken images make it hard to be recognized. Based on the property of shape context, this method can be used for natural scene images of the characters in different type of fonts, even allowing a few deformed in characters. Therefore, this study selected the shape contexts as feature for character recognition in natural scene images. Traditionally, the shape contexts method requires multiple iterations to make feature point matching and each iteration used the Hungarian algorithm to optimize for feature point correspondence. Because the Hungarian algorithm requires a lot of computing time, the time complexity is O (n3). Therefore, this study added the two-dimensional spatial information of feature points, each feature points given the label from different spatial information. Only the corresponding feature point with the same label would be matched, without the need for iteration. The proposed method will improve character recognition speed and efficiency. This study used the data set of ICDAR 2003 (digits 0 through 9 and the uppercase letters A ~ Z, a total of 5100 images) for character recognition. Based on the experimental results, this study got the best shape context parameters and the effect of different parameters of spatial information could be discussed. Compared to the traditional shape contexts of the corresponding method, the proposed method’s recognition rate and the processing speed improved dramatically.