LOGO recognition using textual and visual search

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Hou, Ximing and Shi, Hao (2012) LOGO recognition using textual and visual search. The International Journal of Multimedia and Its Applications, 4 (5). pp. 51-60. ISSN 0975-5934 (print) 0975-5578 (online)

Abstract

The amount of digital data transmitting via interne t has reached an enormous level. In order to conduc t efficient web data analysis, effective web mining t ools are needed. Logos, which represent companies’ brands, are highly regarded in a business world. These logos embedded in ordinary pictures could giv e an indication of popularity of the companies and their products in a region. Therefore, it is imperative to build a computer system to extract company logos from the se pictures. In this paper, a Logo on Map (LoM) system is proposed, which consists of three modules : picture extraction module (PEM), logo matching module (LMM) and web mapping module (WMM). Only the first two modules are covered in this paper. The PEM is based on a keyword textual search while the LMM is a visual search using SIFT (Scale- Invariant Feature Transform) algorithm. The three e xperiments are conducted using different sets of pictures extracted from the Flickr® website. The ex perimental results have proven that visual search i s more accurate than textual search and also demonstr ated that LoM could be used to discover hidden knowledge beyond logos.

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/23574
DOI 0.5121/ijma.2012.4504
Official URL http://airccse.org/journal/jma/4512ijma04.pdf
Subjects Current > FOR Classification > 0801 Artificial Intelligence and Image Processing
Historical > SEO Classification > 8902 Computer Software and Services
Current > Division/Research > College of Science and Engineering
Keywords ResPubID26337, Web mining, Flickr API, textual search, SIFT, algorithms, social media, social networks, networking, visual searches, searching, architecture, recognition, pictures, picture sharing, pictures, LoM, Logo on Map System, Websites, Internet
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