Lockheed Martin Corporation

Other

Ronald William Phillips

James L Nettles

A method for identifying a detected object in multi-dimensional imagery data is disclosed. The method includes, (a) providing (1) a set of comparative feature values associated with one or more known objects in one or more specified observation conditions and (2) a set of observation-related values including (i) a set of feature values for one or more features of an object as observed in an environment, (ii) a set of condition values for one or more conditions of the observation, including one or more of an orientation value, a depression value, a resolution value, and an obscuration value; and (b) generating one or more identification values for the object by comparing the set of feature values to the set of comparative feature values, including compensating for the set of condition values.

Dynamic process for identifying objects in multi-dimensional data

A method for identifying a detected object in multi-dimensional imagery data is disclosed. The method includes, (a) providing (1) a set of comparative feature values associated with one or more known objects in one or -more specified observation conditions and (2) a set of observation-related values including (i) a set of feature values for one or more features of an object as observed in an environment, (ii) a set of condition values for one or more conditions of the observation, including one or more of an orientation value, a depression value, a resolution value, and an obscuration value; and (b) generating one or more identification values for the object by comparing the set of feature values to the set of comparative feature values, including compensating for the set of condition values.

A method employing fuzzy logic for identifying a detected object in LADAR data is disclosed. The method includes extracting a feature of the object; determining a confidence level in the extracted feature; comparing the extracted feature to a corresponding feature of a potential identification using a fuzzy logic process, and identifying the object. The comparison includes weighting at least one rule according to the confidence level in the extracted feature employed by the rule; shifting a membership function for the extracted feature responsive to the confidence level for the extracted feature; and executing the fuzzy logic process to obtain an indication of whether the segmented object corresponds to the potential identification.

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Arlington, TX, United States of America

Ronald William Phillips