Title :
A feature for character recognition based on directional distance distributions
Author :
Oh, Il-Seok ; Suen, Ching Y.
Author_Institution :
Dept. of Comput. Sci., Chonbuk Nat. Univ., Chonju, South Korea
Abstract :
The performance of a character recognition system depends heavily on what features are being used. Though many kinds of features have been developed and their test performances on a standard database have been reported, there is still room to improve the recognition rate by developing an improved feature. The authors propose a new feature based on DDD (directional distance distribution) information. This new concept regards the input pattern array as being circular. It also contains very rich information by encoding in one representation both the white/black distribution and the directional distance distribution. A test performed on the CENPARMI handwritten numeral database showed a promising result of 97.3% recognition with a neural network classifier using the DDD feature
Keywords :
character recognition; feature extraction; image classification; neural nets; CENPARMI handwritten numeral database; character recognition; circular input pattern array; directional distance distributions; encoding; features; neural network classifier; recognition rate; white/black distribution; Buildings; Character recognition; Classification algorithms; Distributed computing; Encoding; Neural networks; Performance evaluation; Spatial databases; Standards development; Testing;
Conference_Titel :
Document Analysis and Recognition, 1997., Proceedings of the Fourth International Conference on
Conference_Location :
Ulm
Print_ISBN :
0-8186-7898-4
DOI :
10.1109/ICDAR.1997.619858
