Translator Disclaimer
Paper
19 January 2009 Script identification of handwritten word images
Author Affiliations +
Proceedings Volume 7247, Document Recognition and Retrieval XVI; 72470Z (2009) https://doi.org/10.1117/12.805682
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States
Abstract
This paper describes a system for script identification of handwritten word images. The system is divided into two main phases, training and testing. The training phase performs a moment based feature extraction on the training word images and generates their corresponding feature vectors. The testing phase extracts moment features from a test word image and classifies it into one of the candidate script classes using information from the trained feature vectors. Experiments are reported on handwritten word images from three scripts: Latin, Devanagari and Arabic. Three different classifiers are evaluated over a dataset consisting of 12000 word images in training set and 7942word images in testing set. Results show significant strength in the approach with all the classifiers having a consistent accuracy of over 97%.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Anurag Bhardwaj, Huaigu Cao, and Venu Govindaraju "Script identification of handwritten word images", Proc. SPIE 7247, Document Recognition and Retrieval XVI, 72470Z (19 January 2009); https://doi.org/10.1117/12.805682
PROCEEDINGS
6 PAGES


SHARE
Advertisement
Advertisement
Back to Top