NDLI: Cursive stroke sequencing for handwritten text documents recognition

Content Provider	IEEE Xplore Digital Library
Author	Panwar, S. Nain, N.
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Eng., Malaviya Nat. Inst. of Technol., Jaipur, India (Panwar, S.; Nain, N.)
Abstract	Text segmentation can be defined as the process of splitting the images of handwritten text document into pieces corresponding to single lines, words and character. This is a very challenging task because in handwritten documents curved text lines appear frequently with different skew and slant angles. After segmentation of word or stroke, also defined as finding the connected components in handwritten text document, we have to sequence the strokes according to the document so that the meaning of the document is preserved. In this paper, We use bottom up grouping approach for segmentation. We have used a novel connectivity strength parameter with depth first search approach for extraction of connected components of the same line from complete connected components of the given document. The exact sequence of connected components is stored in the sequential vector which contains the label of the components. The proposed cursive stroke sequencing technique is implemented and tested on a benchmark IAM database providing encouraging results. Quantitative analysis also shows that this approach gives better results compared to existing segmentation techniques and overcomes the problems encountered in Hill-and-dale writing styles and overlapped and touched lines. The accuracy of the proposed sequencing technique is 98%.
Sponsorship	IEEE Gujarat Sect.
Starting Page	1
Ending Page	4
File Size	741884
Page Count	4
File Format	PDF
e-ISBN	9781479915880
DOI	10.1109/NCVPRIPG.2013.6776232
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-18
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cursive Stroke sequencing Image segmentation Sequential analysis Accuracy Databases Image edge detection Segmentation Connected component Writing Handwritten text recognition Vectors Connectivity strength function
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
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