A modified direction feature for cursive character recognition
conference contribution
posted on 2017-12-06, 00:00 authored by M Blumenstein, X Liu, Brijesh VermaThis paper describes a neural network-based technique for cursive character recognition applicable to segmentation-based word recognition systems. The proposed research builds on a novel feature extraction technique that extracts direction information from the structure of character contours. This principal is extended so that the direction information is integrated with a technique for detecting transitions between background and foreground pixels in the character image. The proposed technique is compared with the standard direction feature extraction technique, providing promising results using segmented characters from the CEDAR benchmark database.
Funding
Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)
History
Start Page
2983End Page
2988Number of Pages
6Start Date
2004-01-01Location
Budapest, HungaryPublisher
Institute of Electrical and Electronics Engineers, Inc.Place of Publication
Piscataway, NJ, USAPeer Reviewed
- Yes
Open Access
- No
External Author Affiliations
Faculty of Informatics and Communication; Griffith University;Era Eligible
- Yes