Scale-space features for object detection

Bradley Pryor Kjell; Arun K. Sood; V. A. Topkar

doi:10.1117/12.45461

1 March 1991 Scale-space features for object detection

Bradley Pryor Kjell, Arun K. Sood, V. A. Topkar

Proceedings Volume 1468, Applications of Artificial Intelligence IX; (1991) https://doi.org/10.1117/12.45461
Event: Orlando '91, 1991, Orlando, FL, United States

Abstract

In many applications, such as remote sensing or target detection, the target objects are small, compact blobs. In the images discussed in this paper these objects are only 6 or fewer pixels across, and the images contain noise and clutter which is similar in appearance to the targets. Since so few pixels comprise an object, the object shape is uncertain, so common shape features are unreliable. To distinguish targets from clutter, features which make use of scale-space have proven useful. The scale-space of an image is a sequence of Gauss-filtered versions of the image, using increasing scales from one image to the next. Experiments show that object features calculated at a single scale. Various moments of the value of the Laplacian at the centroid of a blob were particularly effective for some targets.

Citation Download Citation

Bradley Pryor Kjell, Arun K. Sood, and V. A. Topkar "Scale-space features for object detection", Proc. SPIE 1468, Applications of Artificial Intelligence IX, (1 March 1991); https://doi.org/10.1117/12.45461

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