DocumentCode
2225719
Title
The application of Local Linear Neuro Fuzzy model in recognition of online Persian isolated characters
Author
Daryoush, Koorosh Samimi ; Khademi, Maryam ; Nikookar, Alireza ; Farahani, Aida
Author_Institution
South Tehran Branch, Islamic Azad Univ., Tehran, Iran
Volume
5
fYear
2010
fDate
20-22 Aug. 2010
Abstract
In this paper, we propose an approach for recognizing online Persian isolated characters using LLNF model. Local Linear Neuro Fuzzy (LLNF) Model is a powerful approach for classification tasks. It uses divide-and-conquer strategy to partition the problem space into sub-problems and construct Local Linear Models (LLMs). In order to classify the characters, at first, we extract some generic features of Persian character and build a features vector. Then we construct a LLNF model by the features vector as input data. The constructed LLNF model will be later used to recognize the written letters. Our experimental results for 100 different people show recognition rate of 99.15%.
Keywords
character recognition; divide and conquer methods; feature extraction; fuzzy neural nets; natural language processing; speech recognition; divide and conquer strategy; feature vector; generic features extraction; local linear neuro fuzzy model; online Persian isolated character recognition; written letter; Handwriting recognition; LLNF; Local Linear Neuro-Fuzzy model; Online handwriting recognition; feature extraction; persian character;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location
Chengdu
ISSN
2154-7491
Print_ISBN
978-1-4244-6539-2
Type
conf
DOI
10.1109/ICACTE.2010.5579433
Filename
5579433
Link To Document