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Proceedings Paper

Remote logo detection using angle-distance histograms
Author(s): Sungwook Youn; Jiheon Ok; Sangwook Baek; Seongyoun Woo; Chulhee Lee
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Paper Abstract

Among all the various computer vision applications, automatic logo recognition has drawn great interest from industry as well as various academic institutions. In this paper, we propose an angle-distance map, which we used to develop a robust logo detection algorithm. The proposed angle-distance histogram is invariant against scale and rotation. The proposed method first used shape information and color characteristics to find the candidate regions and then applied the angle-distance histogram. Experiments show that the proposed method detected logos of various sizes and orientations.

Paper Details

Date Published: 19 May 2016
PDF: 6 pages
Proc. SPIE 9874, Remotely Sensed Data Compression, Communications, and Processing XII, 98740K (19 May 2016); doi: 10.1117/12.2225569
Show Author Affiliations
Sungwook Youn, Yonsei Univ. (Korea, Republic of)
Jiheon Ok, Yonsei Univ. (Korea, Republic of)
Sangwook Baek, Yonsei Univ. (Korea, Republic of)
Seongyoun Woo, Yonsei Univ. (Korea, Republic of)
Chulhee Lee, Yonsei Univ. (Korea, Republic of)


Published in SPIE Proceedings Vol. 9874:
Remotely Sensed Data Compression, Communications, and Processing XII
Bormin Huang; Chein-I Chang; Chulhee Lee, Editor(s)

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