NDLI: STRICR-FB, a novel Size-Translation-Rotation-Invariant Character Recognition method

Content Provider	IEEE Xplore Digital Library
Author	Barnes, D. Manic, M.
Copyright Year	2010
Description	Author affiliation: University of Idaho, United States (Barnes, D.; Manic, M.)
Abstract	Character recognition is an active field of research. Applications include point of sale systems, tablet computers, personal digital assistants (PDAs), smart phones, and military applications. Recognizing Asian characters has been pursued since 1984, and difficulties exist in Japanese due to the complexity and numbers of Kanji, Hiragana, and Katakana characters. It is further complicated by differences in size, translation, and rotation. This paper contributes an original approach to constructing feature vectors. The presented Size-Translation-Rotation-Invariant Character Recognition and Feature vector Based STRICR-FB algorithm is based on the Kohonen Winner Take All (WTA) type of unsupervised learning. The algorithm clusters a multidimensional space vectors uniquely derived from the Hiragana characters. The STRICR-FB methodology creates a neural network by design and not by training. This alleviates typical training problems like instability and no convergence. Furthermore, an upper bound degree of closeness is determined by the distance between the two closest unique feature vectors. The STRICR-FB algorithm was implemented in Matlab and uses the Image Processing Toolbox to process the images. The algorithm was tested on the MS Mincho font set. It demonstrated a recognition rate of 90% independent of size, translation, and rotation.
Starting Page	163
Ending Page	168
File Size	322838
Page Count	6
File Format	PDF
ISBN	9781424475605
e-ISBN	9781424475629
DOI	10.1109/HSI.2010.5514573
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-13
Publisher Place	Poland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Multidimensional systems Military computing neural networks Character recognition Application software Unsupervised learning Neural networks feature extraction Clustering algorithms Marketing and sales Personal digital assistants Smart phones pattern recognition
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in