By Topic

Object classification from aerial visual imagery

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ippolito, C. ; Intell. Syst. Div., NASA Ames Res. Center, Moffett Field, CA, USA ; Nefian, A.

Aerial oil pipeline inspection is a dangerous endeavor in the current practice, where a pilot flying in a general aviation class aircraft flies slowly at low altitudes while concurrently looking at the ground for pipeline hazards with the unaided eye; high pilot workload in a dangerous low-speed, low-altitude environment results in an unacceptable number of accidents and loss of life each year. Automation of image acquisition and threat recognition has the potential to reduce pilot workload, improving the safety of the pilots and increasing efficiency. Towards these goals, this paper describes an image classification architecture and algorithm that utilizes several classifiers on different features extracted from the image to automate the threat detection process. The resulting classifier meets the requirement of greater than 80% accuracy in classification. The results will be discussed, and improvements will be proposed for continued research.

Published in:

Sensors, 2010 IEEE

Date of Conference:

1-4 Nov. 2010