Share Email Print

Proceedings Paper

Eigen indexing in satellite recognition
Author(s): Xun Du; Junshui Ma; Mohamed Qasem; Stanley C. Ahalt
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

In many image analysis problems it is possible to take advantage of the structural relationships between various parts of the objects being imaged in order to index the images of the objects. For example, many satellites consists of a main body and outlying sub-components. Thus, in many circumstances satellites can be indexed in a model database by the distinct structural relationships between their sub- components. However, algorithms based on structured sub- components necessitate the use of robust and reliable 2-D image segmentation techniques to successfully partition images into their sub-components. Unfortunately, this segmentation task can be highly problematic for objects with complex components and under harsh, unfavorable lighting conditions. The research presented here describes a new method to compute indices which can be used for image indexing without image segmentation. We use satellite imagery as a convenient image class for which to demonstrate our method. Our method partitions the image into many small equal-area pieces. We refer to this technique as differentiation. Differentiated images result in a set of sub-images that collectively represent the structural information inherent in the image. We prove that a primitive matrix with at most four non-zero eigenvalues can be constructed from the differentiated image. This property (1) significantly reduces storage requirements for a model database, (2) reduces the computational burden of subsequent recognition processes, and (3) supports an efficient and accurate matching procedure. To evaluate the efficiency of our algorithm for a recognition application, we use boundary methods as a feature set evaluation method to quantify the utility of the eigen-indexes obtained by our method as compared to other existing indexing methods.

Paper Details

Date Published: 24 August 1999
PDF: 9 pages
Proc. SPIE 3718, Automatic Target Recognition IX, (24 August 1999); doi: 10.1117/12.359975
Show Author Affiliations
Xun Du, The Ohio State Univ. (United States)
Junshui Ma, The Ohio State Univ. (United States)
Mohamed Qasem, The Ohio State Univ. (United States)
Stanley C. Ahalt, The Ohio State Univ. (United States)

Published in SPIE Proceedings Vol. 3718:
Automatic Target Recognition IX
Firooz A. Sadjadi, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?