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

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

655

Lastpage

659

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on

Conference_Location

Seattle, WA

Print_ISBN

0-7695-1263-1

Type

conf

DOI

10.1109/ICDAR.2001.953871

Filename

953871