Abstract
A comprehensive automatic target recognition (ATR) system using a wavelet transform based target detection preprocessor and a neural network classifier is described. A compact, high-speed optical wavelet processor with full gray scale filter capability, recently developed at JPL has been used for real-time target detection preprocessing. An innovative feature extraction algorithm using the Hermite Moments has been developed and used for neural net classification. The extracted Hermite Moment features, with their greatly reduced dimension and efficient representation, has enabled rapid neural training with test with very high classification and low false alarm rate. Experimental demonstration for face recognition and vehicle classification has been successfully carried out using this ATR system.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
