By Topic

Knowledge-Based Aerial Image Understanding Systems and Expert Systems for Image Processing

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

1 Author(s)
Matsuyama, T. ; Department of Information Engineering, Tohoku University, Sendai, Miyagi 980, Japan

This paper discusses roles of artificial intelligence in the automatic interpretation of remotely sensed imagery. We first discuss several image understanding systems for analyzing complex aerial photographs. The discussion is mainly concerned with knowledge representation and control structure in the aerial image understanding systems: a blackboard model for integrating diverse object detection modules, a symbolic model representation for three-dimensional object recognition, and integration of bottom-up and top-down analyses. Then, a model of expert systems for image processing is introduced that discusses which and what combinations of image processing operators are effective to analyze an image. Various information about image processing techniques is used to find efficient and reliable image analysis processes. In general, two kinds of knowledge, that is, knowledge about objects and about analysis tools (i. e., image processing techniques) are required to realize versatile photointerpretation systems.

Published in:

Geoscience and Remote Sensing, IEEE Transactions on  (Volume:GE-25 ,  Issue: 3 )