Remote logo detection using angle-distance histograms

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


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.

Original languageEnglish
Title of host publicationRemotely Sensed Data Compression, Communications, and Processing XII
EditorsChulhee Lee, Bormin Huang, Chein-I Chang
ISBN (Electronic)9781510601154
Publication statusPublished - 2016
EventRemotely Sensed Data Compression, Communications, and Processing XII - Baltimore, United States
Duration: 2016 Apr 202016 Apr 21

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


OtherRemotely Sensed Data Compression, Communications, and Processing XII
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


Dive into the research topics of 'Remote logo detection using angle-distance histograms'. Together they form a unique fingerprint.

Cite this