Structural Feature Extraction to recognize some of the Offline isolated Handwritten Gujarati Characters using Decision Tree Classifier
Year: 2014
Type: article
Abstract: Large amount of information is prevailing on paper and in an era of digital technology it requires it to store this information in electronic format.Using scanner this information can be digitized.Later any modification in terms of add, editing, removing and searching to it requires a technique or methodology which will identify text from image and convert into ASCII or Unicode.This paper presents recognition of offline handwritten character for Gujarati script using structural features.For proposed experimental work five characters of Gujarati script are considered.Decision tree classifier is proposed for classification.Various phases of character recognition are implemented such as collecting handwritten input, digitization, preprocessing, extracting structural features and recognition.By proposed work authors are able to achieve 88.78% of average success rate for defined five characters.
DOI: 10.5120/17452-8381
Authors: Hetal R.Thaker, C. K. Kumbharana
Institutions: Saurashtra University, Atmiya University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2169197331