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

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

Official URL: https://srj.uitm.edu.my/

Abstract

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.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Yusof, Noor Hazira
UNSPECIFIED
Ibrahim, Zaidah
UNSPECIFIED
Kasiran, Zolidah
UNSPECIFIED
Abu Mangshor, Nur Nabilah
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Instruments and machines
Q Science > QA Mathematics > Web-based user interfaces. User interfaces (Computer systems)
Divisions: Universiti Teknologi MARA, Shah Alam > Research Management Centre (RMC)
Journal or Publication Title: Scientific Research Journal
UiTM Journal Collections: UiTM Journal > Scientific Research Journal (SRJ)
ISSN: 1675-7009
Volume: 14
Number: 2
Page Range: pp. 49-62
Keywords: HOG, SURF and SVM
Date: 2017
URI: https://ir.uitm.edu.my/id/eprint/20416
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20416

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