Patent US5210799A successfully refreshed from Google Patents.
US5210799A
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System and method for ranking and extracting salient contours for target recognition
Assignee: Texas Instruments Inc
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Filing: 1991-03-28
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Granted: 1993-05-11
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Expires: 2011-03-28
Abstract
Abstract A system and method for obtaining salient contours from two-dimensional images acquired by a sensor is disclosed which process the two-dimensional images with an edge detector to produce edgels from each of the images, link the edgels into lists known as contours, compute a saliency value for each of the contours, rank the contours in decreasing order of saliency, and select certain ones of the ranked contours based on the requirements of a particular vision application.
Inventors
- 👤 Kashi Rao
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-10-29 10:52
CPC Classifications
G; G06; G06T; G06T7/00; G06T7/10; G06T7/12; G06T7/181; G06V; G06V10/00; G06V10/20; G06V10/255; G06V10/40; G06V10/44; G06V10/443; G06V10/46; G06V10/462; G06T2207/00; G06T2207/10; G06T2207/10016; G06T2207/10032; G06T2207/10048; G06T2207/20; G06T2207/20016; G06T2207/30; G06T2207/30212
Claims Analysis
Total Claims: 22
Claim 1
Independent Claim
66 words
A method for obtaining salient contours from two-dimensional images acquired by a sensor, comprising the steps of: processing said two-dimensional images with an edge detector to produce edgels from each of said images; linking said edgels into lists known as contours; computing a saliency value for each of said contours; ranking said contours in decreasing order of saliency; and selecting predetermined ones from said ranked contours.
Claim 2
Independent Claim
66 words
A method for obtaining salient contours from two-dimensional images acquired by a sensor, comprising the steps of: processing said two-dimensional images with an edge detector to produce edgels from each of said images; linking said edgels into lists known as contours; computing a saliency value for each of said contours; ranking said contours in decreasing order of saliency; and selecting predetermined ones from said ranked contours.
Claim 3
Dependent Claim
14 words
The method of claim 1, wherein said edge detector is a Canny edge detector.
Claim 4
Dependent Claim
21 words
The method of claim 1, after said step of selecting, further comprising the step of discarding any ranked contours not selected.
Claim 5
Dependent Claim
50 words
The method of claim 1, wherein said step of computing a saliency value for each of said contours further comprises the steps of: ascertaining each of a plurality of saliency measures; applying a predetermined weight to each saliency measure; and determining a saliency value based on said weighted saliency measures.
Claim 6
Dependent Claim
47 words
The method of claim 4, wherein said saliency value, S, is determined as follows: ##EQU5## where ω 1 is the weight for the length saliency measure, ω s is the weight for the smoothness saliency measure, and ω c is the weight for the contrast saliency measure.
Claim 7
Dependent Claim
19 words
The method of claim 4, wherein said step of ascertaining a plurality of saliency measures is performed in parallel.
Claim 8
Dependent Claim
62 words
The method of claim 4, wherein at least one of said plurality of saliency measures includes a smoothness saliency measure, S s , calculated as: ##EQU6## where ΔK is the average change of curvature of the contour, ΔK min is the smallest average change of curvature for all contours, and ΔK max is the largest average change of curvature for all contours.
Claim 9
Dependent Claim
41 words
The method of claim 7, wherein said average change of curvature, ΔK, is calculated with the steps of: computing curvature at each edgel within said contour; determining any change of curvature; and computing an average of said any change of curvature.
Claim 10
Dependent Claim
15 words
The method of claim 8, wherein said step of computing curvature employs a B-spline fitting.
Claim 11
Dependent Claim
28 words
The method of claim 8, wherein said step of determining any change of curvature is accomplished by convolving said computed curvature for each edgel using a difference operator.
Claim 12
Dependent Claim
56 words
The method of claim 4, wherein at least one of said plurality of saliency measures includes a contrast saliency measure, S c , calculated as: ##EQU7## where C is the average contrast of the contour, C min is the smallest average contrast for all contours, and C max is the largest average contrast for all contours.
Claim 13
Dependent Claim
62 words
The method of claim 4, wherein at least one of said plurality of saliency measures includes a length saliency measure, S 1 , calculated as: ##EQU8## where L, the length of the contour, is defined as the number of edgels in that contour, L min is the length of the shortest contour, and L max is the length of the longest contour.
Claim 14
Independent Claim
90 words
A system for object recognition, comprising: a sensor for generating an image of a scene; an edge detector connected to said sensor to detect edgels within said image; a salient contour extractor connected to receive and process said detected edgels into contours, said extractor including a processing unit for determining a saliency value for each of said contours and ranking said contours in decreasing order of saliency; and an object matching system connected to receive preselected ones of said process contours and match them to known contours of predetermined objects.
Claim 15
Independent Claim
90 words
A system for object recognition, comprising: a sensor for generating an image of a scene; an edge detector connected to said sensor to detect edgels within said image; a salient contour extractor connected to receive and process said detected edgels into contours, said extractor including a processing unit for determining a saliency value for each of said contours and ranking said contours in decreasing order of saliency; and an object matching system connected to receive preselected ones of said process contours and match them to known contours of predetermined objects.
Claim 16
Dependent Claim
23 words
The system of claim 13. wherein said salient contour extractor further comprises a linker which links said edgels into lists known as contours.
Claim 17
Dependent Claim
19 words
The system of claim 13, wherein said salient contour extractor comprises a plurality of contour extractors operating in parallel.
Claim 18
Dependent Claim
11 words
The system of claim 13, wherein said sensor is a FLIR.
Claim 19
Dependent Claim
12 words
The system of claim 13, wherein said sensor is a television camera.
Claim 20
Dependent Claim
14 words
The system of claim 13, wherein said edge detector is a Canny edge detector.
Claim 21
Dependent Claim
35 words
The system of claim 13, wherein said processing unit further comprises a computing unit for establishing a saliency value for each of said contours and determining a plurality of saliency measures for each saliency value.
Claim 22
Dependent Claim
14 words
The system of claim 19, wherein said plurality of saliency measures are preselectively weighted.
References Cited (Backward Citations)
USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 1996-05-10 | 1996-11-09 | 1997-05-11 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2000-05-10 | 2000-11-09 | 2001-05-11 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2004-05-10 | 2004-11-09 | 2005-05-11 | $7700.00 | Window Closed / Lapsed |