US6496592B1
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US
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Method for tracking moving object by means of specific characteristics
Assignee: Rheinmetall Air Defence AG
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Filing: 1999-07-13
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Granted: 2002-12-17
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Expires: 2019-07-13
Abstract
Abstract A method for the detection and tracking of moving objects, which can be implemented in hardware computers, is described. The core of the described method is constituted by a gradient integrator ( 42 ), whose contents can be permanently refreshed with a sequence of image sections containing the target object. Different method steps for processing the image sections ( 26 ) reduce the number of required calculation operations and therefore assure sufficient speed of the method.
Inventors
- 👤 Nicola Lanini
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-05 21:35
CPC Classifications
G; G01; G01S; G01S3/00; G01S3/78; G01S3/782; G01S3/785; G01S3/786; G01S3/7864; G01S3/7865
Claims Analysis
Total Claims: 8
Claim 1
Independent Claim
295 words
A method for tracking a moving aerial target on a base of timely variable specific target image features for obtaining target course data, the method comprising the steps of: providing ( 20 ) a series of images ( 22 ); selecting at least one of the images as a selected image; extraction ( 24 ) of an image section ( 26 ) of the selected image; generation ( 35 ) of a gradient selected image ( 37 ) of each extracted image section ( 26 through 34 ); shifting ( 55 ) of the gradient selected image ( 37 ) to obtain a shifted gradient selected image; weighting ( 36 ) of the shifted gradient selected image by a factor (k) for obtaining a weighted gradient image ( 38 ); providing a gradient integrator ( 42 ) having a preceding provided image ( 48 ) according to the selecting, extraction, generation, shifting, and weighting steps; weighting the preceding provided image by a factor of (1−k) to obtain a weighted preceding provided image; addition (+) of the weighted gradient image ( 38 ) to the weighted preceding provided gradient image ( 48 ) for obtaining a resulting gradient image ( 40 ); loading of the resulting gradient image ( 40 ) into the gradient integrator ( 42 ), for obtaining an actualized gradient image ( 46 ); correlation ( 54 ) of the actualized gradient image ( 46 ) with a further gradient image ( 37 ) generated from a subsequently provided selected image ( 22 ) and displaced ( 56 ) prior to correlation ( 54 ), to obtain a correlation signal ( 58 ); and conducting a maximum search ( 60 ) in the correlation signal ( 58 ), for obtaining target course data.
Claim 2
Independent Claim
295 words
A method for tracking a moving aerial target on a base of timely variable specific target image features for obtaining target course data, the method comprising the steps of: providing ( 20 ) a series of images ( 22 ); selecting at least one of the images as a selected image; extraction ( 24 ) of an image section ( 26 ) of the selected image; generation ( 35 ) of a gradient selected image ( 37 ) of each extracted image section ( 26 through 34 ); shifting ( 55 ) of the gradient selected image ( 37 ) to obtain a shifted gradient selected image; weighting ( 36 ) of the shifted gradient selected image by a factor (k) for obtaining a weighted gradient image ( 38 ); providing a gradient integrator ( 42 ) having a preceding provided image ( 48 ) according to the selecting, extraction, generation, shifting, and weighting steps; weighting the preceding provided image by a factor of (1−k) to obtain a weighted preceding provided image; addition (+) of the weighted gradient image ( 38 ) to the weighted preceding provided gradient image ( 48 ) for obtaining a resulting gradient image ( 40 ); loading of the resulting gradient image ( 40 ) into the gradient integrator ( 42 ), for obtaining an actualized gradient image ( 46 ); correlation ( 54 ) of the actualized gradient image ( 46 ) with a further gradient image ( 37 ) generated from a subsequently provided selected image ( 22 ) and displaced ( 56 ) prior to correlation ( 54 ), to obtain a correlation signal ( 58 ); and conducting a maximum search ( 60 ) in the correlation signal ( 58 ), for obtaining target course data.
Claim 3
Dependent Claim
30 words
The method in accordance with claim 1 , wherein processing the image section ( 26 ) is done by a mean curvature process ( 28 ) for initializing the method.
Claim 4
Dependent Claim
27 words
The method in accordance with claim 1 , wherein processing the image section ( 26 ) is subjected to a Gauss-like low pass filtering ( 32 ).
Claim 5
Dependent Claim
29 words
The method in accordance with claim 1 , wherein obtaining a pattern of the tracked target by means of non-maximum suppression ( 50 ) of the integrator gradient image.
Claim 6
Dependent Claim
32 words
The method in accordance with claim 4 , wherein reducing image pixels of patterns to image pixels having a minimum value; and, writing over all remaining image pixels with the value zero.
Claim 7
Dependent Claim
57 words
The method in accordance with claim 4 , wherein searching the image pixels for patterns for their connected in lines of a preselected minimum length; and, writing over all image pixels having a value which is not equal to zero and which are not connected in a line of a preselected minimum length with the value zero.
Claim 8
Dependent Claim
38 words
The method in accordance with claim 1 , wherein writing over values in gradient images, which values exceed the maximum value in the integrator image stored in the gradient integrator by a preselected value with the value zero.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2005-12-16 | 2006-06-17 | 2006-12-17 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2009-12-16 | 2010-06-17 | 2010-12-17 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2013-12-16 | 2014-06-17 | 2014-12-17 | $7700.00 | Window Closed / Lapsed |