DocumentCode :
146379
Title :
Recognition of similar shaped isolated handwritten Gurumukhi characters using machine learning
Author :
Kaur, Rupinderjit ; Gujral, Shruti
Author_Institution :
Comput. Sci. & Eng., Chandigarh Univ., Chandigarh, India
fYear :
2014
fDate :
25-26 Sept. 2014
Firstpage :
251
Lastpage :
256
Abstract :
Existence of similar shaped handwritten characters in any script affects its automated recognition. Effective recognition of similar shaped characters increases overall performance of automated handwritten character recognition. It is intensive research area because of its application in wide ambit of real human beings problems like postal address interpretation and signature verification in bank cheque processing etc. In this work, people in the age group of 20-50 years were asked to write characters of Gurumukhi Script in their natural writing style. Preprocessing steps were applied on the collected data and zoning based structural & region features were extracted. Data set was created using the extracted features and recognition was done using Random Forest and C4.5 machine learning algorithms.
Keywords :
feature extraction; handwritten character recognition; learning (artificial intelligence); natural language processing; random processes; C4.5 machine learning algorithms; Gurumukhi script; automated handwritten character recognition; bank cheque processing; features extraction; natural writing style; postal address interpretation; random forest; signature verification; similar shaped isolated handwritten Gurumukhi characters recognition; Accuracy; Character recognition; Feature extraction; Handwriting recognition; Shape; Support vector machines; Vegetation; Feature Extraction; Machine Learning; Region Based Features; Zoning Based Structural Features;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Confluence The Next Generation Information Technology Summit (Confluence), 2014 5th International Conference -
Conference_Location :
Noida
Print_ISBN :
978-1-4799-4237-4
Type :
conf
DOI :
10.1109/CONFLUENCE.2014.6949050
Filename :
6949050
Link To Document :
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