Segmentation and Feature Extraction for Cursive English Handwriting Recognition

Pritam Dhande, Reena Kharat

Abstract


This paper aims to represent the various techniques
of optical character recognition for cursive English handwriting.OCR is a challenging research area in pattern recognition
and image processing. In OCR, images of printed ,handwritten
or typed text are scanned and converted into machine readable
text. There are scanners with inbuilt OCR for printed documents
but not for handwritten documents. Character recognition of
handwritten cursive English script is a very challenging task. In
cursive English handwriting, the characters in a word are connected to each other. So the segmentation and feature extraction
of cursive English script is much difficult.

Full Text:

PDF

References


Abhishek Bala and Rajib Saha,“An Improved Method for Handwritten

Document Analysis using Segmentation, Baseline Recognition and Writing Pressure Detection”,6th International Conference On Advances In

Computing Communications, ICACC 2016, 6-8 September 2016, Cochin,

India,Elsevier-2016.

Kanchan Keisham and Sunanda Dixit,“Recognition of Handwritten English Text Using Energy Minimisation”, Information Systems Design and

Intelligent Applications, Advances in Intelligent Systems and Computing,

Bangalore, India,Springer-2016.

Nibaran Das,Sandip Pramanik,Subhadip Basu,Punam Kumar Saha,

“Recognition of handwritten Bangla basic characters and digits using

convex hull based feature set”, 2009 International conference on Artificial

intelligence and pattern recognition(AIPR-09).

Subhadip Basu, Nibaran Das, Ram Sarkar, Mahantapas Kundu, Mita

Nasipuri, Dipak Kumar Basu,“A hierarchical approach to recognition of

handwritten Bangla characters”, Elsevier -2009

Namrata Dave,“Segmentation Methods for Hand Written Character

Recognition”, International Journal of Signal Processing, Image Processing and Pattern Recognition Vol. 8, No. 4 (2015), pp. 155-164.

Nafiz Arica, Student Member, IEEE, and Fatos T. Yarman-Vural, Senior

Member, IEEE,“Optical Character Recognition for Cursive Handwriting”,

IEEE transactions on pattern analysis and machine intelligence, vol. 24,

no. 6, june 2002

G. Louloudisa, B.Gatosb, I.Pratikakisb, C.Halatsisa,“Text line and word

segmentation of handwritten documents”a Department of Informatics

and Telecommunications, University of Athens, Greece Computational

Intelligence Laboratory, Institute of Informatics and Telecommunications,

National Center for Scientific Research Demokritos, 15310Athens,Greece

Subhash Panwar and Neeta Naina,“A Novel Segmentation Methodology for Cursive Handwritten Documents”, IETE JOURNAL OF RESEARCH,VOL 60-NO 6- NOVDEC 2014

Bilan Zhua, Arti Shivramb, Venu Govindarajub and Masaki

Nakagawaa,“Online Handwritten Cursive Word Recognition Using

Segmentation-free and Segmentation-based Methods”, 978-1-4799-6100-

/15/31.00-2015 IEEE

Hong Lee n, BrijeshVerma,“Binary segmentation algorithm for English

cursive handwriting recognition ”2011 ElsevierLtd


Refbacks

  • There are currently no refbacks.


Copyright © IJETT, International Journal on Emerging Trends in Technology