Accession Number : ADA299738
Title : Outdoor Landmark Recognition using Hybrid Fractal Vision System and Neural Networks.
Descriptive Note : Quarterly Progress rept. Jan-Mar 95,
Corporate Author : NORTH CAROLINA STATE UNIV AT RALEIGH DEPT OF ELECTRICAL AND COMPUTER ENGINEERI NG
Personal Author(s) : Luo, Ren C.
PDF Url : ADA299738
Report Date : MAR 1995
Pagination or Media Count : 9
Abstract : A hybrid fractal vision system is being developed for landmark detection and recognition in natural scenes. At the current quarter of research, a reconfigurable neural network is being designed to recognize landmarks. The fractal model detected the landmarks for cluttered images, and the neural network would recognize those landmarks. A brief description of the theoretical design of this Reconfigurable Neural Network is given here. Also, some of the initial results obtained by testing the neural network on real image data are included with this report. A new learning method is also being developed and briefly reported here. Automatic recognition systems can be useful in both military and commercial domains. Tasks such as military surveillance, automatic target recognition, automatic vehicle navigation, material handling, inspection, data compression/decompression, autonomous robot navigation, etc are some of the practical issues directly enhanced by automatic and robust vision systems.
Descriptors : *FRACTALS, *NEURAL NETS, *TARGET RECOGNITION, *LANDFORMS, *OUTDOOR, FREQUENCY, IMAGE PROCESSING, SPATIAL DISTRIBUTION, ROBOTS, NAVIGATION, RECOGNITION, HYBRID SYSTEMS, VISION, VEHICLES, DATA COMPRESSION, SURVEILLANCE, AUTOMATIC, AUTOMATIC PILOTS, DECOMPRESSION, NAVIGATION REFERENCE, MATERIALS HANDLING.
Subject Categories : Cybernetics
Target Direction, Range and Position Finding
Distribution Statement : APPROVED FOR PUBLIC RELEASE