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

     Research Journal of Applied Sciences, Engineering and Technology


Pedestrian and Object Detection Using a Spatial Filter in the Dark Environment

P. Selvarani and Sairam Natarajan
School of Computing, Sastra University, Thanjavur, India
Research Journal of Applied Sciences, Engineering and Technology  2013  2:357-360
http://dx.doi.org/10.19026/rjaset.5.4958  |  © The Author(s) 2013
Received: April 12, 2012  |  Accepted: May 06, 2012  |  Published: January 11, 2013

Abstract

This study dedicates a new approach for detecting the pedestrians and the objects in the dark environment using a spatial filter. Detecting an actual position of an object and a person in the dark region is an atomic challenge for many researchers. To detect the objects and the persons, a spatial filter is utilized. The basic idea of the spatial filter is adapted by varying its radii of the dark region. Based on the radii’s variation, the persons and the objects are detected. Finally, the actual position of detecting objects and persons are segmented using object compensation. Extensive experiments have been carried out on an object equipped with an infrared/digital camera and preliminarily tested in different situations. This proposed method is achieved 90.7% accuracy in detecting an actual position of the human and the object in the dark area.

Keywords:

Dark regions, IR/digital image, segmentation, spatial filter,


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