Logo recognition and localization in real-world images by using visual patterns

Wei Ta Chu; Tsung Che Lin

doi:10.1109/ICASSP.2012.6288047

Logo recognition and localization in real-world images by using visual patterns

Wei Ta Chu, Tsung Che Lin

Department of Computer Science and Information Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

10 Citations (Scopus)

Abstract

By describing spatial relationships between feature points, we present promising logo recognition and localization, which are verified based on two state-of-the-art datasets. Given features points on the query logo, similar features on test images are efficiently found by locality sensitive hashing. After filtering out outliers, candidate regions are found by the mean-sift algorithm, and each region is compared with the logo by jointly considering visual word histogram and visual patterns. Evaluation results show that visual patterns more appropriately describe logos and provide better performance than previous approaches.

Original language	English
Title of host publication	2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings
Pages	973-976
Number of pages	4
DOIs	https://doi.org/10.1109/ICASSP.2012.6288047
Publication status	Published - 2012 Oct 23
Event	2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Kyoto, Japan Duration: 2012 Mar 25 → 2012 Mar 30

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)	1520-6149

Other

Other	2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
Country/Territory	Japan
City	Kyoto
Period	12-03-25 → 12-03-30

All Science Journal Classification (ASJC) codes

Software
Signal Processing
Electrical and Electronic Engineering

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10.1109/ICASSP.2012.6288047

Cite this

Chu, W. T., & Lin, T. C. (2012). Logo recognition and localization in real-world images by using visual patterns. In 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings (pp. 973-976). [6288047] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2012.6288047

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title = "Logo recognition and localization in real-world images by using visual patterns",

abstract = "By describing spatial relationships between feature points, we present promising logo recognition and localization, which are verified based on two state-of-the-art datasets. Given features points on the query logo, similar features on test images are efficiently found by locality sensitive hashing. After filtering out outliers, candidate regions are found by the mean-sift algorithm, and each region is compared with the logo by jointly considering visual word histogram and visual patterns. Evaluation results show that visual patterns more appropriately describe logos and provide better performance than previous approaches.",

author = "Chu, {Wei Ta} and Lin, {Tsung Che}",

year = "2012",

month = oct,

day = "23",

doi = "10.1109/ICASSP.2012.6288047",

language = "English",

isbn = "9781467300469",

series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

pages = "973--976",

booktitle = "2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings",

note = "2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 ; Conference date: 25-03-2012 Through 30-03-2012",

}

Chu, WT & Lin, TC 2012, Logo recognition and localization in real-world images by using visual patterns. in 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings., 6288047, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pp. 973-976, 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012, Kyoto, Japan, 12-03-25. https://doi.org/10.1109/ICASSP.2012.6288047

Logo recognition and localization in real-world images by using visual patterns. / Chu, Wei Ta; Lin, Tsung Che.

2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings. 2012. p. 973-976 6288047 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

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AU - Chu, Wei Ta

AU - Lin, Tsung Che

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N2 - By describing spatial relationships between feature points, we present promising logo recognition and localization, which are verified based on two state-of-the-art datasets. Given features points on the query logo, similar features on test images are efficiently found by locality sensitive hashing. After filtering out outliers, candidate regions are found by the mean-sift algorithm, and each region is compared with the logo by jointly considering visual word histogram and visual patterns. Evaluation results show that visual patterns more appropriately describe logos and provide better performance than previous approaches.

AB - By describing spatial relationships between feature points, we present promising logo recognition and localization, which are verified based on two state-of-the-art datasets. Given features points on the query logo, similar features on test images are efficiently found by locality sensitive hashing. After filtering out outliers, candidate regions are found by the mean-sift algorithm, and each region is compared with the logo by jointly considering visual word histogram and visual patterns. Evaluation results show that visual patterns more appropriately describe logos and provide better performance than previous approaches.

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T2 - 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012

Y2 - 25 March 2012 through 30 March 2012

ER -

Logo recognition and localization in real-world images by using visual patterns

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