Automatic model construction for object recognition using inverse synthetic aperture radar images

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. Comparing with manually constructed recognition models used by most researchers in the computer vision community, this approach is suitable for constructing an object recognition system capable of recognizing a large number of objects. Results of experiments using the automatically constructed models in object recognition are presented.