Text localisation for roman words from shop signage / Nurbaity Sabri ... [et al.]

Text localisation determinesthe location of the text in an image. This process is performed prior to text recognition. Localising text on shop signage is a challenging task since the images of the shop signage consist of complex background, and the text occurs in various font types, sizes, and co...

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Main Authors:	Yusof, Noor Hazira, Ibrahim, Zaidah, Kasiran, Zolidah, Abu Mangshor, Nur Nabilah
Format:	Article
Language:	English
Published:	Research Management Institute (RMI) 2017
Subjects:	Instruments and machines Web-based user interfaces. User interfaces (Computer systems)
Online Access:	http://ir.uitm.edu.my/id/eprint/20416/ http://ir.uitm.edu.my/id/eprint/20416/2/AJ_NURBAITY%20SABRI%20SRJ%2017.pdf

id	uitm-20416
recordtype	eprints
spelling	uitm-204162019-03-11T08:20:55Z http://ir.uitm.edu.my/id/eprint/20416/ Text localisation for roman words from shop signage / Nurbaity Sabri ... [et al.] Yusof, Noor Hazira Ibrahim, Zaidah Kasiran, Zolidah Abu Mangshor, Nur Nabilah Instruments and machines Web-based user interfaces. User interfaces (Computer systems) Text localisation determinesthe location of the text in an image. This process is performed prior to text recognition. Localising text on shop signage is a challenging task since the images of the shop signage consist of complex background, and the text occurs in various font types, sizes, and colours. Two popular texture features that have been applied to localise text in scene images are a histogram of oriented gradient (HOG) and speeded up robust features (SURF). A comparative study is conducted in this paper to determine which is better with support vector machine (SVM) classifier. The performance of SVM is influenced by its kernel function and another comparative study is conducted to identify the best kernel function. The experiments have been conducted using primary data collected by the authors. Resultsindicate that HOG with quadratic kernel function localises text for shop signage better than SURF. Research Management Institute (RMI) 2017 Article PeerReviewed text en http://ir.uitm.edu.my/id/eprint/20416/2/AJ_NURBAITY%20SABRI%20SRJ%2017.pdf Yusof, Noor Hazira and Ibrahim, Zaidah and Kasiran, Zolidah and Abu Mangshor, Nur Nabilah (2017) Text localisation for roman words from shop signage / Nurbaity Sabri ... [et al.]. Scientific Research Journal, 14 (2). pp. 49-62. ISSN 1675-7009
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Instruments and machines Web-based user interfaces. User interfaces (Computer systems)
spellingShingle	Instruments and machines Web-based user interfaces. User interfaces (Computer systems) Yusof, Noor Hazira Ibrahim, Zaidah Kasiran, Zolidah Abu Mangshor, Nur Nabilah Text localisation for roman words from shop signage / Nurbaity Sabri ... [et al.]
description	Text localisation determinesthe location of the text in an image. This process is performed prior to text recognition. Localising text on shop signage is a challenging task since the images of the shop signage consist of complex background, and the text occurs in various font types, sizes, and colours. Two popular texture features that have been applied to localise text in scene images are a histogram of oriented gradient (HOG) and speeded up robust features (SURF). A comparative study is conducted in this paper to determine which is better with support vector machine (SVM) classifier. The performance of SVM is influenced by its kernel function and another comparative study is conducted to identify the best kernel function. The experiments have been conducted using primary data collected by the authors. Resultsindicate that HOG with quadratic kernel function localises text for shop signage better than SURF.
format	Article
author	Yusof, Noor Hazira Ibrahim, Zaidah Kasiran, Zolidah Abu Mangshor, Nur Nabilah
author_facet	Yusof, Noor Hazira Ibrahim, Zaidah Kasiran, Zolidah Abu Mangshor, Nur Nabilah
author_sort	Yusof, Noor Hazira
title	Text localisation for roman words from shop signage / Nurbaity Sabri ... [et al.]
title_short	Text localisation for roman words from shop signage / Nurbaity Sabri ... [et al.]
title_full	Text localisation for roman words from shop signage / Nurbaity Sabri ... [et al.]
title_fullStr	Text localisation for roman words from shop signage / Nurbaity Sabri ... [et al.]
title_full_unstemmed	Text localisation for roman words from shop signage / Nurbaity Sabri ... [et al.]
title_sort	text localisation for roman words from shop signage / nurbaity sabri ... [et al.]
publisher	Research Management Institute (RMI)
publishDate	2017
url	http://ir.uitm.edu.my/id/eprint/20416/ http://ir.uitm.edu.my/id/eprint/20416/2/AJ_NURBAITY%20SABRI%20SRJ%2017.pdf
first_indexed	2023-09-18T23:04:35Z
last_indexed	2023-09-18T23:04:35Z
_version_	1777418397479337984

Text localisation for roman words from shop signage / Nurbaity Sabri ... [et al.]

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