Linking broken character borders with variable sized masks to improve recognition

摘要

A novel border-following algorithm is used to reconstruct the borders and missing links of noisy and broken handwritten digits. When combined with a suitable rejection threshold, improved performance from handwritten character classifiers is achieved. Experimental results are given which show the effectiveness of the method, raising recognition rates by an additional 5% for handwritten digits in the presence of gaps and noise.