Home            Contact us            FAQs
    
      Journal Home      |      Aim & Scope     |     Author(s) Information      |      Editorial Board      |      MSP Download Statistics

     Research Journal of Applied Sciences, Engineering and Technology


High-Speed Recognition Algorithm Based on BRISK and Saliency Detection for Aerial Images

Teng-Jiao Xiao, Dan-Pei Zhao, Jun Shi and Ming Lu
Image Processing Center, School of Astronautics, Beihang University, Beijing, China
Research Journal of Applied Sciences, Engineering and Technology  2013  23:5469-5473
http://dx.doi.org/10.19026/rjaset.5.4221  |  © The Author(s) 2013
Received: November 29, 2012  |  Accepted: January 17, 2013  |  Published: May 28, 2013

Abstract

A fast ground object recognition method for aerial images, taking airports, oil depots, harbors, etc., as research objects, is proposed in this study based on BRISK and the visual saliency detection. According to the characteristics of aerial images, such as high resolution and complex background interference, saliency detection is applied to select the candidate object region where the target may exist. Therefore, it can reduce the searching range effectively. And then, BRISK matching method is used to recognize the object efficiently. A variety of experiments under different interference factors are carried out based on the typical object database of aerial images in this study. Experimental results show that the proposed algorithm can not only maintain the validity of BRISK features under the conditions of rotation, scale, illumination and viewpoint changes, but also shorten the matching time, satisfying real-time demand.

Keywords:

Aerial images, BRISK matching, object recognition, saliency detection,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
Submit Manuscript
   Information
   Sales & Services
Home   |  Contact us   |  About us   |  Privacy Policy
Copyright © 2024. MAXWELL Scientific Publication Corp., All rights reserved