Corner detection for identification of man-made objects in noisy aerial images

Isaac N. Bankman; Eric W. Rogala

doi:10.1117/12.477038

25 July 2002 Corner detection for identification of man-made objects in noisy aerial images

Isaac N. Bankman, Eric W. Rogala

Proceedings Volume 4726, Automatic Target Recognition XII; (2002) https://doi.org/10.1117/12.477038
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

Corner detection is an essential feature extraction step in many image understanding applications including aerial image analysis and manufactured part inspection. Available corner detectors require the user to set critical manual thresholds, degrade under significant noise levels, or introduce high computational complexity. We present a nonlinear corner detection algorithm that does not require prior image information or any threshold to be set by the user. It provides 100% correct corner detection and fewer than 1 false positive corner per image when the contrast to noise ratio of the image is 6 or more, under Gaussian white noise.

Citation Download Citation

Isaac N. Bankman and Eric W. Rogala "Corner detection for identification of man-made objects in noisy aerial images", Proc. SPIE 4726, Automatic Target Recognition XII, (25 July 2002); https://doi.org/10.1117/12.477038

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available