NDLI: SIGMA: Spatial Integrated Matching Association algorithm for logo detection

Content Provider	IEEE Xplore Digital Library
Author	Pengfei Xu Hongxun Yao Rongrong Ji
Copyright Year	2010
Description	Author affiliation: School of Computer Science and Technology, Harbin Institute of Technology, China (Pengfei Xu; Hongxun Yao; Rongrong Ji)
Abstract	In this paper, we adopt the integration model of spatial feature correlations to order the indexing and matching features, and address the computational ineffectiveness and inefficiency of local features based logo detection methods. We propose a Spatial InteGrated Matching Association algorithm (SIGMA) for logo detection in natural scene that contains extremely variances in viewpoints, illuminations and occlusions. Our SIGMA algorithm consists of two phases: the Spatial InteGrated (SIG) phase and the Matching Association (MA) phase. The SIG phase integrates spatial correlations in feature representation, while the MA phase improves the matching performance by ordering an optimized matching sequence. We have collected a logo dataset containing 2,400 photos with 12 logo categories from Flickr, and experimental results demonstrate that the performance of proposed approach outperforms the state-of-the-art approaches on the dataset.
Starting Page	1086
Ending Page	1089
File Size	561292
Page Count	4
File Format	PDF
ISBN	9781424442959
ISSN	15206149
DOI	10.1109/ICASSP.2010.5495345
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer vision Layout Feature extraction Videos Flowcharts Computer science Indexing Lighting Trademarks Image recognition logo detection feature set matching local feature presentation spatial correlation tree SIGMA
Content Type	Text
Resource Type	Article

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