Detection of new image objects in video sequences using neural networks

Sameer Singh; Markos Markou; John F. Haddon

doi:10.1117/12.382914

14 April 2000 Detection of new image objects in video sequences using neural networks

Sameer Singh, Markos Markou, John F. Haddon

Proceedings Volume 3962, Applications of Artificial Neural Networks in Image Processing V; (2000) https://doi.org/10.1117/12.382914
Event: Electronic Imaging, 2000, San Jose, CA, United States

Abstract

The detection of image segmented objects in video sequences is constrained by the a priori information available with a classifier. An object recognizer labels image regions based on texture and shape information about objects for which historical data is available. The introduction of a new object would culminate in its misclassification as the closest possible object known to the recognizer. Neural networks can be used to develop a strategy to automatically recognize new objects in image scenes that can be separated from other data for manual labeling. In this paper, one such strategy is presented for natural scene analysis of FLIR images. Appropriate threshold tests for classification are developed for separating known from unknown information. The results show that very high success rates can be obtained using neural networks for the labeling of new objects in scene analysis.

Citation Download Citation

Sameer Singh, Markos Markou, and John F. Haddon "Detection of new image objects in video sequences using neural networks", Proc. SPIE 3962, Applications of Artificial Neural Networks in Image Processing V, (14 April 2000); https://doi.org/10.1117/12.382914

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