NDLI: Combining RtL and LtR HMMs to recognise handwritten Farsi words of small- and medium-sized vocabularies

Content Provider	IET Digital Library
Author	Arani, Seyed Ali Asghar Abbaszadeh Kabir, Ehsanollah Ebrahimpour, Reza
Abstract	In this study, a method for holistic recognition of handwritten Farsi words is proposed, which fuses the outputs of right-to-left (RtL) and left-to-right (LtR) hidden Markov models (HMMs). The experimental results on 16,000 images of 200 names of Iranian cities, from the ‘Iranshahr 3’ are presented and compared with those methods using only RtL or LtR models. Experimental results show that the main sources of error are similar beginnings or similar endings of the words. Since RtL and LtR models when dealing with the words behave differently, there is notable error diversity between the two classifiers in such a way that their combination increases the recognition rate. Compared to the RtL-HMM, the product of output scores of the RtL and LtR-HMMs reduces the classification error to about 6, 6 and 3%, for three different feature sets. A subjective error analysis on the results is also provided.
Starting Page	925
Ending Page	932
Page Count	8
ISSN	17519632
Volume Number	12
e-ISSN	17519640
Issue Number	Issue 6, Sep (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/12/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2017.0645
Journal	IET Computer Vision
Publisher Date	2018-04-30
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Classification Error Combined RtL-LtR HMMs Computer Vision And Image Processing Technique Error Diversity Handwriting Recognition Handwritten Farsi Word Recognition Hidden Markov Model Image Classification Image Recognition Iranian Cities Iranshahr 3 Left-to-right Hidden Markov Model Markov Processes Medium-sized Vocabularies Natural Language Processing Right-to-left Hidden Markov Model Small-sized Vocabularies Subjective Error Analysis
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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