Patent US6028956A successfully refreshed from Google Patents.
US6028956A
Expired / Lapsed
US
⏱️ 0.0 years remaining
Object location and span determination method and apparatus which determines a location and span of an object in an image
Assignee: Open Text SA
•
Filing: 1997-04-04
•
Granted: 2000-02-22
•
Expires: 2017-04-04
Abstract
Abstract Apparatus and method for determining a location and span of an object in an image. The determined location and span of the object are used to process the image to simplify a subsequent classification process.
Inventors
- 👤 Alexander Shustorovich
- 👤 Christopher W. Thrasher
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 14:07
CPC Classifications
G; G06; G06V; G06V30/00; G06V30/10; G06V30/14; G06V30/146; G06V30/147; G06V30/16; G06V30/166
Claims Analysis
Total Claims: 27
Claim 1
Independent Claim
110 words
A method for processing an image containing an object to be subsequently classified, the method comprising steps of: a) generating windows; b) applying the generated windows to the image to form windowed images; c) determining a position of the object by providing the windowed images to a trained learning mechanism; d) determining a span of the object by providing the windowed images to the trained learning mechanism; e) normalizing the object based on the determined span to form a normalized object; and f) centering the normalized object within a classification window based on the determined position, wherein a subsequent classification of the object may be performed on the classification window.
Claim 2
Independent Claim
110 words
A method for processing an image containing an object to be subsequently classified, the method comprising steps of: a) generating windows; b) applying the generated windows to the image to form windowed images; c) determining a position of the object by providing the windowed images to a trained learning mechanism; d) determining a span of the object by providing the windowed images to the trained learning mechanism; e) normalizing the object based on the determined span to form a normalized object; and f) centering the normalized object within a classification window based on the determined position, wherein a subsequent classification of the object may be performed on the classification window.
Claim 3
Dependent Claim
70 words
The method of claim 1 wherein the step of generating windows includes sub-steps of: i) determining a first horizontal position at a first horizontal side of the image; ii) applying a window having a predetermined size at the first horizontal position of the image; iii) determining a next horizontal position; iv) applying a window having the predetermined size at the next horizontal position; and v) repeating sub-steps (iii) and (iv).
Claim 4
Dependent Claim
52 words
The method of claim 2 wherein the image is defined by a two-dimensional array of pixels, and wherein the sub-step of determining a next horizontal position includes a step of moving the window a predetermined number of pixels in a first horizontal direction away from the first horizontal side of the image.
Claim 5
Dependent Claim
22 words
The method of claim 1 wherein the the trained learning mechanism is trained to determine the position and span of an object.
Claim 6
Dependent Claim
56 words
The method of claim 1 wherein the steps of (c) determining a position of the object by providing the windowed images to a trained learning mechanism, and (d) determining a span of the object by providing the windowed images to a trained learning mechanism, collectively, includes the step of post-processing outputs of the trained learning mechanism.
Claim 7
Dependent Claim
73 words
The method of claim 5 wherein the sub-step of post-processing outputs of the trained learning mechanism includes steps of: A) filtering the outputs of the trained learning mechanism to generate filtered outputs; B) thresholding the filtered outputs to generate thresholded, filtered outputs; C) determining the position the object based on a center of mass of the thresholded, filtered outputs; and D) determining the span of the object based on the thresholded, filtered outputs.
Claim 8
Dependent Claim
27 words
The method of claim 1 further comprising steps of: a1) detecting sub-images within the image; a2) normalizing the detected sub-images; and a3) reassembling the normalized detected sub-images.
Claim 9
Dependent Claim
31 words
The method of claim 1 further comprising a step of: a1) iteratively applying finer resolution sub-images of the image, as an input, until the position of the object can be determined.
Claim 10
Dependent Claim
22 words
The method of claim 1 wherein the position of the object determined is a horizontal coordinate of a center of the object.
Claim 11
Independent Claim
107 words
A method for classifying an object contained in an image, the method comprising steps of: a) generating windows; b) applying the generated windows to the image to form windowed images; c) determining a position of the object by providing the windowed images to a trained learning mechanism; d) determining a span of the object by providing the windowed images to the trained learning mechanism; e) normalizing the object based on the determined span to form a normalized object; f) centering the normalized object within a classification window based on the determined position; and g) classifying the object based on the classification window to generate a classification result.
Claim 12
Independent Claim
107 words
A method for classifying an object contained in an image, the method comprising steps of: a) generating windows; b) applying the generated windows to the image to form windowed images; c) determining a position of the object by providing the windowed images to a trained learning mechanism; d) determining a span of the object by providing the windowed images to the trained learning mechanism; e) normalizing the object based on the determined span to form a normalized object; f) centering the normalized object within a classification window based on the determined position; and g) classifying the object based on the classification window to generate a classification result.
Claim 13
Dependent Claim
33 words
The method of claim 10 further comprising a step of: h) postprocessing the classification result based on at least one of (i) a confidence measure, and (ii) the determined position of the object.
Claim 14
Dependent Claim
54 words
The method of claim 10 further comprising steps of: a1) detecting sub-images within the image; a2) normalizing the detected sub-images; a3) reassembling the normalized detected sub-images; and h) postprocessing the classification result based on at least one of (i) a confidence measure, (ii) the determined position of the object, and (iii) a sub-image boundary.
Claim 15
Dependent Claim
22 words
The method of claim 10 wherein the position of the object determined is a horizontal coordinate of a center of the object.
Claim 16
Independent Claim
100 words
A device for processing an image having an object to be classified, the device comprising: a) means for generating windows and for applying the generated windows to the image to form windowed images; b) means for determining a position and a span of the object by providing the windowed images to a trained learning mechanism; c) means for normalizing the object based on the determined span to form a normalized object; and d) means for centering the normalized object within a classification window based on the determined position, wherein the normalized object centered within the classification window may be classified.
Claim 17
Independent Claim
100 words
A device for processing an image having an object to be classified, the device comprising: a) means for generating windows and for applying the generated windows to the image to form windowed images; b) means for determining a position and a span of the object by providing the windowed images to a trained learning mechanism; c) means for normalizing the object based on the determined span to form a normalized object; and d) means for centering the normalized object within a classification window based on the determined position, wherein the normalized object centered within the classification window may be classified.
Claim 18
Dependent Claim
14 words
The device of claim 14 wherein the trained leaning mechanism is a neural network.
Claim 19
Dependent Claim
45 words
The device of claim 15 wherein the neural network includes an input layer of neurons, a Gabor layer of neurons having inputs coupled with outputs of the neurons of the input layer, at least one hidden layer of neurons, and an output layer of neurons.
Claim 20
Dependent Claim
113 words
The device of claim 15 wherein the neural network includes: i) an input layer of neurons, ii) a Gabor layer of neurons having inputs coupled with outputs of the neurons of the input layer, iii) a first hidden layer of neurons having inputs coupled with outputs of the neurons of the Gabor layer, iv) a second hidden layer of neurons having inputs coupled with outputs of the neurons of the first hidden layer, v) a third hidden layer of neurons having inputs coupled with outputs of the neurons of the second hidden layer, and vi) an output layer of neurons having inputs coupled with outputs of the neurons of the third hidden layer.
Claim 21
Dependent Claim
53 words
The device of claim 14 wherein the means for determining a position and a span of the object by providing the windowed images to a trained learning mechanism includes: i) the trained learning mechanism providing outputs based on the windowed images; and ii) means for post-processing the outputs of the trained learning mechanism.
Claim 22
Dependent Claim
74 words
The device of claim 18 wherein the means for post-processing includes: A) means for filtering the outputs of the trained learning mechanism to generate filtered outputs; B) means for thresholding the filtered outputs to generate thresholded, filtered outputs; C) means for determining the position of the object based on a center of mass of the thresholded, filtered outputs; and D) means for determining the span of the object based on the thresholded, filtered outputs.
Claim 23
Dependent Claim
31 words
The device of claim 14 further comprising: a1) means for detecting sub-images within the image; a2) means for normalizing the detected sub-images; and a3) means for reassembling the normalized detected sub-images.
Claim 24
Dependent Claim
23 words
The device of claim 14 further comprising: e) means for classifying the object based on the classification window to generate a classification result.
Claim 25
Dependent Claim
32 words
The device of claim 21 further comprising: f) means for postprocessing the classification result based on at least one of (i) a confidence measure, and (ii) the determined position of the object.
Claim 26
Dependent Claim
60 words
The device of claim 21 further comprising: a1) means for detecting sub-images within the image; a2) means for normalizing the detected sub-images; a3) means for reassembling the normalized detected sub-images; and f) means for postprocessing the classification result based on at least one of (i) a confidence measure, (ii) the determined position of the object, and (iii) a sub-image boundary.
Claim 27
Dependent Claim
21 words
The device of claim 14 wherein the position of the object is a horizontal coordinate of a center of the object.
References Cited (Backward Citations)
US4933977A
Cited
US5119438A
Cited
US5131073A
Cited
US5151951A
Cited
US5052043A
Cited
US5239593A
Cited
US5105468A
Cited
US5440651A
Cited
US5500905A
Cited
US5299269A
Cited
US5337370A
Cited
US5245672A
Cited
US5542006A
Cited
USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2003-02-21 | 2003-08-23 | 2004-02-22 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2007-02-21 | 2007-08-23 | 2008-02-22 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2011-02-21 | 2011-08-23 | 2012-02-22 | $7700.00 | Window Closed / Lapsed |