Separation of single-touching handwritten numeral strings based on structural features

In this paper, we develop a new method to separate single-touching handwritten numeral strings with two numerals using structural features. A binary image of a single-touching handwritten numeral string is preprocessed with an efficient algorithm for smoothing, linearization and detection of structural points of image contours. The touching region of a single-touching handwritten numeral string is determined based on distribution of the structural points in the handwritten numeral string. A candidate touching point is preselected based on the geometrical information of a special structural point in the touching region. In some cases, the left or right lateral numeral of a single-touching handwritten numeral string can be recognized. The recognition information can be utilized to correct the position of the candidate touching point. We have tested our method on image samples taken from the U.S. National Institute of Science and Technology (NIST) database. We used 500 sample images for training and obtained a correct separation rate of 99.1%. For 3287 test samples not used for training the correct separation rate was 97.2%. (C) 1998 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.