NDLI: Recognition of cursive video text using a deep learning framework

Content Provider	IET Digital Library
Author	Mirza, Ali Siddiqi, Imran
Abstract	This study focuses on cursive text recognition appearing in videos, using a complete framework of deep neural networks. While mature video optical character recognition systems (V-OCRs) are available for text in non-cursive scripts, recognition of cursive scripts is marked by many challenges. These include complex and overlapping ligatures, context-dependent shape variations and presence of a large number of dots and diacritics. The authors present an analytical technique for recognition of cursive caption text that relies on a combination of convolutional and recurrent neural networks trained in an end-to-end framework. Text lines extracted from video frames are preprocessed to segment the background and are fed to a convolutional neural network for feature extraction. The extracted feature sequences are fed to different variants of bi-directional recurrent neural networks along with the ground truth transcription to learn sequence-to-sequence mapping. Finally, a connectionist temporal classification layer is employed to produce the final transcription. Experiments on a data set of more than 40,000 text lines from 11,192 video frames of various News channel videos reported an overall character recognition rate of 97.63%. The proposed work employs Urdu text as a case study but the findings can be generalised to other cursive scripts as well.
Starting Page	3444
Ending Page	3455
Page Count	12
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 14, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/14
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.1070
Journal	IET Image Processing
Publisher Date	2020-09-02
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Background Segmentation Bi-directional Recurrent Neural Network Character Recognition Rate Complex Ligatures Computer Vision And Image Processing Technique Content-based Retrieval Context-dependent Shape Variations Convolutional Network Convolutional Neural Network Cursive Caption Text Cursive Scripts Cursive Video Text Deep Learning Document Processing Technique End-to-end Framework Feature Extraction Feature Sequence Extraction Image Recognition Image Segmentation Information Retrieval Technique Learning in AI Mature V-OCRs Neural Computing Technique News Channel Videos Noncursive Scripts Optical Character Recognition Overlapping Ligatures Recurrent Neural Nets Sequence-to-sequence Mapping Text Analysis Text Line Extraction Text Region Textual Content-based Retrieval System Urdu Text Video Frames Video Optical Character Recognition System Video Retrieval Video Signal Processing Video Text Recognition
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

Multi-mode neural network for human action recognition

Efficient and unified license plate recognition via lightweight deep neural network

Fatigue driving recognition network: fatigue driving recognition via convolutional neural network and long short-term memory units

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

Multi-dimensional data modelling of video image action recognition and motion capture in deep learning framework

Capturing the spatio-temporal continuity for video semantic segmentation

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

Button recognition with texture feature based on spiking neural network

Deep template matching for offline handwritten Chinese character recognition

Recognition of cursive video text using a deep learning framework

Similar Documents

Multi-mode neural network for human action recognition

Efficient and unified license plate recognition via lightweight deep neural network

Fatigue driving recognition network: fatigue driving recognition via convolutional neural network and long short-term memory units

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

Multi-dimensional data modelling of video image action recognition and motion capture in deep learning framework

Capturing the spatio-temporal continuity for video semantic segmentation

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

Button recognition with texture feature based on spiking neural network

Deep template matching for offline handwritten Chinese character recognition

Recognition of cursive video text using a deep learning framework