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Urdu Caption Text Detection using Textural Features

Published: 27 March 2018 Publication History

Abstract

The amount of multimedia data has increased manifolds in the recent years. This calls for development of efficient retrieval techniques. Among various aspects of content based retrieval, textual content appearing in videos and images serves as a powerful semantic index. Development of such a retrieval system requires detection of text regions, recognition of detected text and generation of indices on keywords. Among these, the focus of the present study lies on detection of textual content from video frames. More specifically, we target the caption Urdu text appearing in News and entertainment channels. A series of image analysis operations is first carried out to identify candidate text blocks in the image. Features extracted from text and non-text regions using Gabor filters and Curvelet transform are fed to two classifiers namely artificial neural network and support vector machine. Evaluations on a database of 1000 video frames reported promising precision and recall.

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cover image ACM Other conferences
MedPRAI '18: Proceedings of the 2nd Mediterranean Conference on Pattern Recognition and Artificial Intelligence
March 2018
135 pages
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • IAPR: International Association for Pattern Recognition

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 March 2018

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Author Tags

  1. Artificial Urdu Text
  2. Curvelet Transform
  3. Gabor Filters
  4. Text Detection
  5. Textural Features

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Cited By

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  • (2022)Text Recognition Using Image Processing Technology for Visiting CardInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology10.32628/CSEIT228652(488-492)Online publication date: 5-Dec-2022
  • (2021)Automated text detection from big data scene videos in higher education: a practical approach for MOOCs case studyJournal of Computing in Higher Education10.1007/s12528-021-09294-yOnline publication date: 3-Sep-2021
  • (2021)A system for detection of moving caption text in videos: a news use caseMultimedia Tools and Applications10.1007/s11042-021-10856-6Online publication date: 22-Apr-2021
  • (2021)Urdu signboard detection and recognition using deep learningMultimedia Tools and Applications10.1007/s11042-020-10175-281:9(11965-11987)Online publication date: 6-Jan-2021
  • (2020)Detection and recognition of cursive text from video framesEURASIP Journal on Image and Video Processing10.1186/s13640-020-00523-52020:1Online publication date: 28-Aug-2020
  • (2020)Urdu-Text Detection and Recognition in Natural Scene Images Using Deep LearningIEEE Access10.1109/ACCESS.2020.29942148(96787-96803)Online publication date: 2020
  • (2020)Recognition of Cursive Caption Text Using Deep Learning - A Comparative Study on Recognition UnitsPattern Recognition and Artificial Intelligence10.1007/978-3-030-59830-3_14(156-167)Online publication date: 9-Oct-2020
  • (2019)Impact of Pre-Processing on Recognition of Cursive Video TextPattern Recognition and Image Analysis10.1007/978-3-030-31332-6_49(565-576)Online publication date: 22-Sep-2019

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