Title :
Feature extraction based on fuzzy set theory for handwriting recognition
Author :
Gomes, Natanael Rodrigues ; Ling, Lee Luan
Author_Institution :
Univ. Estadual de Campinas, Sao Paulo, Brazil
fDate :
6/23/1905 12:00:00 AM
Abstract :
The paper presents a method based on fuzzy set theory for extracting features from handwritten words. After the feature extraction and word segmentation process, a handwritten word is represented by an ordered sequence of line segments. For each of these segments, membership values for fuzzy sets are calculated, representing different types of curved lines and straight lines. The position of the line segments in a letter or piece of a letter resulting from the word segmentation is also evaluated by means of fuzzy sets. Fuzzy hidden Markov models are employed to classify the handwritten words. A database comprising handwritten words extracted from Brazilian bank checks is used to test the proposed system
Keywords :
feature extraction; fuzzy set theory; handwriting recognition; hidden Markov models; word processing; Brazilian bank checks; curved lines; feature extraction; fuzzy hidden Markov models; fuzzy set theory; handwriting recognition; handwritten words; line segments; membership values; ordered sequence; straight lines; word segmentation process; Databases; Feature extraction; Fuzzy set theory; Fuzzy sets; Handwriting recognition; Hidden Markov models; Image recognition; Image segmentation; System testing; Vocabulary;
Conference_Titel :
Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7695-1263-1
DOI :
10.1109/ICDAR.2001.953871
