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
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;
Conference_Titel :
Communication, Information & Computing Technology (ICCICT), 2015 International Conference on
Conference_Location :
Mumbai
Print_ISBN :
978-1-4799-5521-3
DOI :
10.1109/ICCICT.2015.7045738