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Please use this identifier to cite or link to this item: http://hdl.handle.net/1812/353

Title: A STUDY ON NORMALIZATION AND FEATURE EXTRACTION TECHNIQUES FOR THE RECOGNITION OF ISOLATED KANNADA HANDWRITTEN NUMERALS
Authors: Surekha Patil
Meenakshi Patil
Keywords: Handwritten numeral recognition
Normalization
Aspect ratio
Direction features
Gradient features
Issue Date: 2007
Abstract: The evaluation of various techniques is important to select the correct options in developing character recognition system. Normalization is an important preprocessing technique for character recognition and feature extraction is the core of OCR. In this paper we conduct experiments for different normalization functions and different feature extraction strategies. It is hoped that this study improves the performance of character recognition system and will find wider use to the researchers.
Description: Proceeding of the 2nd International Conference on Informatics (Informatics 2007), 27th-28th November 2007, Hilton Petaling Jaya Hotel, Petaling Jaya, Selangor, Malaysia. Page T1-105 - T1-109
URI: http://dspace.fsktm.um.edu.my/handle/1812/353
ISBN: 978-983-43491-1-0
Appears in Collections:Informatics 2007

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