NDLI: Urdu handwritten text recognition: a survey

Content Provider	IET Digital Library
Author	Husnain, Mujtaba Missen, Malik Muhammad Saad Mumtaz, Shahzad Coustaty, Mickaël Luqman, Muzzamil Ogier, Jean Marc
Abstract	Work on the problem of handwritten text recognition in Urdu script has been an active research area. A significant progress is made in this interesting and challenging field in the last few years. In this study, the authors presented a comprehensive survey for a number of offline and online handwritten text recognition systems for Urdu script written in Nastaliq font style from 2004 to 2019. Following features make their contribution worthwhile and unique among the reviews of a similar kind: (i) their review classifies the existing studies based on types of recognition systems used for Urdu handwritten text, (ii) it covers a very different outlook of the recognition process of the Urdu handwritten text at different granularity levels (e.g. character, word, ligature, or sentence level), (iii) this review article also presents each of surveyed articles in following dimensions: the task performed, its granularity level, dataset used, results obtained, and future dimensions, and (iv) lastly it gives the summary of the surveyed articles according to the granularity levels, publishing years, related tasks or subtasks, and types of classifiers used. In the end, major challenges and tasks related to Urdu handwritten text recognition approaches are also discussed in detail.
Starting Page	2291
Ending Page	2300
Page Count	10
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 11, Sep (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.0401
Journal	IET Image Processing
Publisher Date	2020-04-15
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Challenging Field Computer Vision And Image Processing Technique Different Granularity Levels Document Image Processing Document Processing Technique Granularity Level Handwritten Character Recognition Image Recognition Interesting Field Natural Language Processing Online Handwritten Text Recognition System Optical Character Recognition Recognition Process Surveyed Articles Text Analysis Urdu Handwritten Text Recognition Approach Urdu Script
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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

Handwritten Hindi character recognition: a review

Segmentation-based recognition system for handwritten Bangla and Devanagari words using conventional classification and transfer learning

H-WordNet: a holistic convolutional neural network approach for handwritten word recognition

Empirical mode decomposition for online handwritten signature verification

Chinese cursive character detection method

Learning one-to-many stylised Chinese character transformation and generation by generative adversarial networks

Detection and segmentation of touching handwritten Gurmukhi script

Online Handwritten Character Recognition of Devanagari and Telugu Characters using Support Vector Machines

Deep template matching for offline handwritten Chinese character recognition

Urdu handwritten text recognition: a survey

Similar Documents

Handwritten Hindi character recognition: a review

Segmentation-based recognition system for handwritten Bangla and Devanagari words using conventional classification and transfer learning

H-WordNet: a holistic convolutional neural network approach for handwritten word recognition

Empirical mode decomposition for online handwritten signature verification

Chinese cursive character detection method

Learning one-to-many stylised Chinese character transformation and generation by generative adversarial networks

Detection and segmentation of touching handwritten Gurmukhi script

Online Handwritten Character Recognition of Devanagari and Telugu Characters using Support Vector Machines

Deep template matching for offline handwritten Chinese character recognition

Urdu handwritten text recognition: a survey