Remote logo detection using angle-distance histograms

Sungwook Youn; Jiheon Ok; Sangwook Baek; Seongyoun Woo; Chulhee Lee

doi:10.1117/12.2225569

19 May 2016 Remote logo detection using angle-distance histograms

Sungwook Youn, Jiheon Ok, Sangwook Baek, Seongyoun Woo, Chulhee Lee

Proceedings Volume 9874, Remotely Sensed Data Compression, Communications, and Processing XII; 98740K (2016) https://doi.org/10.1117/12.2225569
Event: SPIE Commercial + Scientific Sensing and Imaging, 2016, Baltimore, MD, United States

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.

Citation Download Citation

Sungwook Youn, Jiheon Ok, Sangwook Baek, Seongyoun Woo, and Chulhee Lee "Remote logo detection using angle-distance histograms", Proc. SPIE 9874, Remotely Sensed Data Compression, Communications, and Processing XII, 98740K (19 May 2016); https://doi.org/10.1117/12.2225569

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