DocumentCode
1718251
Title
A fuzzy based classification scheme for unconstrained handwritten Devanagari character recognition
Author
Shelke, Sushama ; Apte, Shaila
Author_Institution
Electron. & Telecommun., NBN Sinhgad Sch. of Eng., Pune, India
fYear
2015
Firstpage
1
Lastpage
6
Abstract
The large data set and similar structural features of the characters in Devanagari script demand a highly efficient classification and recognition system. This paper presents a novel approach for the recognition of unconstrained handwritten Devanagari characters. The system is based on multi-stage classification scheme. The classification stages categorize the characters into smaller groups. The classification is done using two stages, first stage is based on fuzzy inference system and second stage is based on structural parameters. The fuzzy system improves the classification over crisp classification. The classified characters are passed to the feature extraction stage. The final stage implements feed forward neural network for character recognition. The recognition accuracy achieved by the proposed method is 96.95%.
Keywords
feature extraction; feedforward neural nets; fuzzy reasoning; fuzzy systems; handwritten character recognition; natural language processing; pattern classification; character structural features; feature extraction stage; feedforward neural network; fuzzy based classification scheme; fuzzy inference system; multistage classification scheme; structural parameters; unconstrained handwritten Devanagari character recognition; Biological neural networks; Character recognition; Feature extraction; Fuzzy logic; Neurons; Training; fuzzy logic; handwritten Devanagari characters recognition; neural network; structural features;
fLanguage
English
Publisher
ieee
Conference_Titel
Communication, Information & Computing Technology (ICCICT), 2015 International Conference on
Conference_Location
Mumbai
Print_ISBN
978-1-4799-5521-3
Type
conf
DOI
10.1109/ICCICT.2015.7045738
Filename
7045738
Link To Document