METHOD OF IDENTIFYING A TRACKED OBJECT FOR USE IN PROCESSING HYPERSPECTRAL DATA

• US 20140050352A1
• Filed: 08/17/2012
• Published: 02/20/2014
• Est. Priority Date: 08/17/2012
• Status: Active Grant

• Current Assignee: GE Aviation Systems LLC (GE Aerospace)
• Original Assignee: GE Aviation Systems LLC (GE Aerospace)
• Inventors: Buehler, Eric Daniel, Occhipinti, Benjamin Thomas, Kuczynski, Konrad Robert
• Granted Patent: US 9,122,929 B2
• Time in Patent Office: Days
• US Class Current: 382/103
• CPC Class Codes: G01J 3/02 Details
• CPC Class Codes: G01N 21/359 using near infrared light
• CPC Class Codes: G06V 20/13 Satellite images

Abstract

The invention relates a method of identifying a tracked object that has a known database of hyperspectral and spatial information. The method associates an identifier with the tracked object; selects a parameter associated with the hyperspectral or spatial information of the tracked object; detects a deviation in the selected parameter; compares the deviation with the database; and if the deviation exceeds a predetermined threshold, assigns a new identifier to the tracked object, and if the deviation does not exceed the predetermined threshold, continues tracking the tracked object.

Claims

1. A method of identifying a tracked object comprising:

tracking an object using an image sensor, wherein the tracked object has a known database of hyperspectral and spatial information;

associating an identifier with the tracked object;

selecting at least one parameter associated with the hyperspectral or spatial information of the tracked object;

detecting a deviation in the selected at least one parameter;

comparing the deviation with the database; and

if the deviation exceeds a predetermined threshold, assigning a new identifier to the tracked object, and if the deviation does not exceed the predetermined threshold, continue tracking the tracked object.

2. The method of claim 1 and the step of updating the database with a change in the at least one parameter.

3. The method of claim 1 and the step of identifying the step of detecting a deviation in the selected at least one parameter as an event.

4. The method of claim 1 where the at least one parameter includes one of color, contrast, brightness, shape, velocity, direction, size, location.

5. The method of claim 1 where the step of comparing the deviation with the database is performed with one of Spectral Angle Mapping (SAM), Spectral Information Divergence (SID), Zero Mean Differential Angle (ZMDA), Mahalanobis Distance, Bhattacharyya Distance.