Title :
Classification-based segmentation of ZIP codes
Author :
Saifullah, Yousuf ; Manry, Michael T.
Author_Institution :
Dept. of Electr. Eng., Texas Univ., Arlington, TX, USA
Abstract :
In this paper a system for the segmentation of unconstrained handwritten ZIP codes is presented. A binarization algorithm is described that utilizes the bimodal nature of the input 256 gray level histogram. ZIP code images are scaled to a standard size for further processing. Objects that are not comparable to the size of numerals are classified as noise and removed. An algorithm that segments broken or touching characters is presented. Several trial segmentations of each ZIP code are produced. A character classifier is used to determine which trial segmentation is most likely to be correct
Keywords :
character recognition; image coding; image segmentation; postal services; USA postal service; ZIP codes images; binarization algorithm; character classifier; classification-based segmentation; histogram; unconstrained handwritten character recognition; Character recognition; Code standards; Histograms; Image databases; Image segmentation; Noise generators; Pixel; Postal services; Robot vision systems; Sorting;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
