NDLI: A preprocessing method for printed Tamil documents: Skew correction and textual classification

Content Provider	IEEE Xplore Digital Library
Author	Ramanan, M. Ramanan, A. Charles, E.Y.A.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci., Univ. of Jaffna, Jaffna, Sri Lanka (Ramanan, A.; Charles, E.Y.A.) \|\| Dept. of Comput. Sci., Eastern Univ., Trincomalee, Sri Lanka (Ramanan, M.)
Abstract	An Optical character recognition (OCR) consists of the phases: preprocessing and segmentation, feature extraction, classification and post-processing. This paper focuses on preprocessing and segmentation tasks which plays a major role in the subsequent processes of an OCR. The objective of preprocessing and segmentation is to improve the quality of the input image. In addition this phase removes unnecessary portions of the input image that would otherwise complicate the subsequent steps of OCR and reduce the overall recognition rate. Preprocessing and segmentation step consists many sub processes namely, image binarisation, noise removal, skew detection and correction, page segmentation, text or non-text classification, line segmentation, word segmentation and character segmentation. This paper proposes a new method to calculate the skew angle for skew correction. In addition this paper proposes a more accurate method to segment the input image as blocks and classify the blocks as text or non-text. The skew angle is calculated on the scanned document using Wiener filter, smearing technique and Radon transform. Document image is segmented into blocks using run length smearing algorithm and connected component analysis. Features such as basic, density and HOG are extracted from each block for text and non-text classification. The proposed methods are tested on 54 documents. The testing results show a recognition rate of 96.30% for skew detection and correction whereas the recognition rate is 99.18% for text or non-text classification with binary SVMs using RBF kernel.
Starting Page	495
Ending Page	500
File Size	1211883
Page Count	6
File Format	PDF
ISBN	9781509019496
e-ISBN	9781509019502
DOI	10.1109/IntelCIS.2015.7397266
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-12-12
Publisher Place	Egypt
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Skew correction Image segmentation Chlorine Printed Tamil documents Textual classification Optical character recognition software
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

Challenges of broken characters in character segmentation method for Gujarati printed documents

An optical character recognition of machine printed Oriya script

Skew detection, page segmentation, and script classification of printed document images

A New Method on the Segmentation and Recognition of Chinese Characters for Automatic Chinese Seal Imprint Retrieval

Efficient system for Devnagari script segmentation

A hybrid decision tree for printed Tamil character recognition using SVMs

An object/segment oriented skew-correction technique for document images

Script independent text pre-processing and segmentation for OCR

OCRMPD: OCR system for Myanmar printed document image with a novel segmentation method and hierarchical classification scheme

A preprocessing method for printed Tamil documents: Skew correction and textual classification

Similar Documents

Challenges of broken characters in character segmentation method for Gujarati printed documents

An optical character recognition of machine printed Oriya script

Skew detection, page segmentation, and script classification of printed document images

A New Method on the Segmentation and Recognition of Chinese Characters for Automatic Chinese Seal Imprint Retrieval

Efficient system for Devnagari script segmentation

A hybrid decision tree for printed Tamil character recognition using SVMs

An object/segment oriented skew-correction technique for document images

Script independent text pre-processing and segmentation for OCR

OCRMPD: OCR system for Myanmar printed document image with a novel segmentation method and hierarchical classification scheme

A preprocessing method for printed Tamil documents: Skew correction and textual classification