The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
May. 21, 2002
Filed:
Jun. 17, 1999
Raytheon Company, Lexington, MA (US);
Abstract
A multi-resolution feature extraction method and apparatus. In the illustrative embodiment, the feature extractor includes circuitry for receiving and transforming a time variant data signal into a multi-resolution data signal. The multi-resolution data signal is compared to each of a plurality of object templates. The system then generates a feature vector based on a correlation of the multi-resolution data signal to one of the object templates. The multi-resolution feature extraction method employs object templates formed by transforming time variant image data for each of a plurality of objects into a respective multi-resolution template and averaging all templates for each respective object. The method includes steps for transforming an incoming time variant data signal into a multi-resolution data signal, comparing the multi-resolution data signal to each of the object templates, and generating a feature vector when the multi-resolution data signal correlates to one of the object templates. In a more specific implementation, the method further includes the steps of calculating a confusion matrix (CM), classifying the feature vectors as one of the objects to thereby produce classified objects responsive to the CM, and selecting a target from the classified objects. A multi-resolution feature extractor according to the present invention employs object templates formed by transforming time variant image data for each of a plurality of objects into a respective multi-resolution template and averaging all templates for each respective object to thereby generate object templates.