Wavelet-Based Hierarchical Organization of Large Image Databases: ISAR and Face Recognition

Abstract

We present a method for constructing efficient hierarchical organization of image databases for fast recognition and classification. The method combines a wavelet preprocessor with a Tree-Structured-Vector-Quantization for clustering. We show results of application of the method to ISAR data from ships and to face recognition based on photograph databases. In the ISAR case we show how the method constructs a multi-resolution aspect graph for each target. This paper was presented at the "SPIE's 12th Annual International Symposium on Aerospace/Defense Sensing, Simulation, and Controls (Aerosense'98)", April 13-17, 1998, Orlando, Florida.