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.
| Original language | English |
|---|---|
| Title of host publication | Remotely Sensed Data Compression, Communications, and Processing XII |
| Editors | Chulhee Lee, Bormin Huang, Chein-I Chang |
| Publisher | SPIE |
| ISBN (Electronic) | 9781510601154 |
| DOIs | |
| Publication status | Published - 2016 |
| Event | Remotely Sensed Data Compression, Communications, and Processing XII - Baltimore, United States Duration: 2016 Apr 20 → 2016 Apr 21 |
Publication series
| Name | Proceedings of SPIE - The International Society for Optical Engineering |
|---|---|
| Volume | 9874 |
| ISSN (Print) | 0277-786X |
| ISSN (Electronic) | 1996-756X |
Other
| Other | Remotely Sensed Data Compression, Communications, and Processing XII |
|---|---|
| Country/Territory | United States |
| City | Baltimore |
| Period | 16/4/20 → 16/4/21 |
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