Artificial Urdu Text Detection and Localization from Individual Video Frames
In current era of technology, information acquisition from images and videos become most important task due to the rapid development of data mining and machine learning.The information can be either textual, visual, or combination of these. Text appearing in images or videos is a significant source...
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doaj-b0414fb14fd9491dbc686cbf489ecd672020-11-24T22:43:55ZengMehran University of Engineering and TechnologyMehran University Research Journal of Engineering and Technology0254-78212413-72192018-04-0137242943810.22581/muet1982.1802.18216Artificial Urdu Text Detection and Localization from Individual Video FramesSalahuddin Unar0Akhtar Hussain Jalbani1Muhammad Moazzam Jawaid2Mohsin Shaikh3Asghar Ali Chandio4School of Computer Science and Technology, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China.Department of Information Technology, Quaid-e-Awam University of Engineering, Science and Technology, NawabshahDepartment of Computer System Engineering, Mehran University of Engineering and Technology, JamshoroQuaid-e-Awam University College of Engineering, Science and Technology, Larkano.School of Engineering and Information Technology, University of New South Wales, Canberra, AustraliaIn current era of technology, information acquisition from images and videos become most important task due to the rapid development of data mining and machine learning.The information can be either textual, visual, or combination of these. Text appearing in images or videos is a significant source of information and plays a vital role to perceive it. Developing a unified method to detect the text is hard, as textual properties (i.e. font, size, color, illumination, orientation, etc.) may vary with the complex background. So far, multimedia and computer vision community unable yet to standardize any ideal approach to extract the text smoothly. In this paper, a novel method is proposed to detect and localize artificial Urdu text in individual video frames. Firstly, Sobel and Canny edge detection operators are applied to input frame and are merged with MSER (Maximally Stable Extremal Region) detected regions. Next, geometric constraints are applied to eliminate obvious non-text regions with large and small variations. Further refining of non-text regions is achieved by stroke width transform. SVM (Support Vector Machine) classifier is trained to classify text and non-text objects. Finally, bounding boxes are used to localize the text.Experimental results show that the proposed method is robust and efficient than state-of-the-art methods.http://publications.muet.edu.pk/index.php/muetrj/article/view/216 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Salahuddin Unar Akhtar Hussain Jalbani Muhammad Moazzam Jawaid Mohsin Shaikh Asghar Ali Chandio |
spellingShingle |
Salahuddin Unar Akhtar Hussain Jalbani Muhammad Moazzam Jawaid Mohsin Shaikh Asghar Ali Chandio Artificial Urdu Text Detection and Localization from Individual Video Frames Mehran University Research Journal of Engineering and Technology |
author_facet |
Salahuddin Unar Akhtar Hussain Jalbani Muhammad Moazzam Jawaid Mohsin Shaikh Asghar Ali Chandio |
author_sort |
Salahuddin Unar |
title |
Artificial Urdu Text Detection and Localization from Individual Video Frames |
title_short |
Artificial Urdu Text Detection and Localization from Individual Video Frames |
title_full |
Artificial Urdu Text Detection and Localization from Individual Video Frames |
title_fullStr |
Artificial Urdu Text Detection and Localization from Individual Video Frames |
title_full_unstemmed |
Artificial Urdu Text Detection and Localization from Individual Video Frames |
title_sort |
artificial urdu text detection and localization from individual video frames |
publisher |
Mehran University of Engineering and Technology |
series |
Mehran University Research Journal of Engineering and Technology |
issn |
0254-7821 2413-7219 |
publishDate |
2018-04-01 |
description |
In current era of technology, information acquisition from images and videos become most important task due to the rapid development of data mining and machine learning.The information can be either textual, visual, or combination of these. Text appearing in images or videos is a significant source of information and plays a vital role to perceive it. Developing a unified method to detect the text is hard, as textual properties (i.e. font, size, color, illumination, orientation, etc.) may vary with the complex background. So far, multimedia and computer vision community unable yet to standardize any ideal approach to extract the text smoothly. In this paper, a novel method is proposed to detect and localize artificial Urdu text in individual video frames. Firstly, Sobel and Canny edge detection operators are applied to input frame and are merged with MSER (Maximally Stable Extremal Region) detected regions. Next, geometric constraints are applied to eliminate obvious non-text regions with large and small variations. Further refining of non-text regions is achieved by stroke width transform. SVM (Support Vector Machine) classifier is trained to classify text and non-text objects. Finally, bounding boxes are used to localize the text.Experimental results show that the proposed method is robust and efficient than state-of-the-art methods. |
url |
http://publications.muet.edu.pk/index.php/muetrj/article/view/216 |
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