Title :
Segmentation and recognition for handwritten 2-letter state names
Author :
Tsuruoka, S. ; Kimura, F. ; Miyake, Y. ; Shridhar, M. ; Chen, Z.
Author_Institution :
Fac. of Eng., Mie Univ., Japan
Abstract :
Proposes a new splitting algorithm for two-letter state name (state-name abbreviation) segmentation to recognize the state name on mail pieces. The merit of this algorithm is that the splitting point is located near the center of 0-projections, and it is especially effective for images in which the widths of each latter are different, such as “IN”, “HI”, “WI” and “MI”. The performance of the algorithm is tested by real USPS mail envelopes. The correct segmentation rate obtained by the segmentation algorithm is 95.4% (91.7% by Kimura´s splitting method) for two-letter state name images (932 images)
Keywords :
handwriting recognition; image segmentation; optical character recognition; postal services; 0-projections; handwritten 2-letter state names; image recognition; image segmentation; letter widths; mail envelopes; splitting algorithm; state-name abbreviation; Algorithm design and analysis; Character recognition; Clustering algorithms; Handwriting recognition; Histograms; Image databases; Image processing; Image segmentation; Postal services; Testing;
Conference_Titel :
Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on
Conference_Location :
Tsukuba Science City
Print_ISBN :
0-8186-4960-7
DOI :
10.1109/ICDAR.1993.395613
