@inproceedings{82d5e51140e441e2aa0749cfa2bbc805,
title = "A fuzzy features based online handwritten Bangla word recognition framework",
abstract = "Handwriting recognition is one of the most important ways to ease the handling of information between man and machine. Online handwriting recognition can be a very attractive method when people feel inconvenient using keyboards to handle information with computing devices. The most complicated task associated with online Bangla handwritten recognition is to separate the adjacent characters and vowel signs from one another within a Bangla word. This problem becomes more complicated due to the variations of writing style of individuals. In this paper, we propose a framework to recognize handwritten Bangla words in real time considering different writing styles. We used fuzzy linguistic rules in order to recognize Bangla handwritten words. Evaluation result for various writing styles reveals that the propose framework can recognize Bangla handwritten words with 77\% accuracy.",
keywords = "aggregation, fuzzy features, Handwritten recognition, online recognition, segmentation",
author = "Kanchan Chowdhury and Lamia Alam and Shyla Sarmin and Safayet Arefin and Hoque, \{Mohammed Moshiul\}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 18th International Conference on Computer and Information Technology, ICCIT 2015 ; Conference date: 21-12-2015 Through 23-12-2015",
year = "2016",
month = jun,
day = "8",
doi = "10.1109/ICCITechn.2015.7488119",
language = "English",
series = "2015 18th International Conference on Computer and Information Technology, ICCIT 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "484--489",
booktitle = "2015 18th International Conference on Computer and Information Technology, ICCIT 2015",
}