Automatic model construction for object recognition using ISAR images

Author

Zhang, Shujun ; Bhanu, Bir

Author_Institution

Coll. of Eng., California Univ., Riverside, CA, USA

Volume

4

fYear

1996

fDate

25-29 Aug 1996

Firstpage

169

Abstract

This paper discusses model construction for object recognition using ISAR images. A learning-from-examples approach is used to construct recognition models of the objects from their ISAR data. Given a set of ISAR data of an object of interest, structural features are extracted from the images. Statistical analysis and geometrical reasoning are then used to analyze the features to find spatial and statistical invariance so that a structural model of the object suitable for object recognition can be constructed. Results of experiments using the automatically constructed model in object recognition are presented

Keywords

feature extraction; image representation; learning by example; learning systems; object recognition; radar target recognition; spatial reasoning; statistical analysis; synthetic aperture radar; ISAR images; automatic model construction; geometrical reasoning; inverse synthetic aperture radar; learning-from-examples; model representation; object recognition; spatial invariance; statistical analysis; statistical invariance; structural feature extraction; Azimuth; Data mining; Educational institutions; Feature extraction; Frequency; Object recognition; Solid modeling; Statistical analysis; Testing; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 1996., Proceedings of the 13th International Conference on

Conference_Location

Vienna

ISSN

1051-4651

Print_ISBN

0-8186-7282-X

Type

conf

DOI

10.1109/ICPR.1996.547255

Filename

547255