US5548667A
Expired / Lapsed
US
⏱️ 0.0 years remaining
Image processing system and method thereof in which three dimensional shape is reproduced from two dimensional image data
Assignee: Sony Corp
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Filing: 1994-09-07
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Granted: 1996-08-20
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Expires: 2014-09-07
Abstract
Abstract The image processing system has a unit for photographing an object in two dimensions, a feature extraction unit for extracting features from the two-dimensional image data from the photographing means, and a three-dimensional shape reproduction unit. The feature extraction unit refers to feature points given to the object to extract the features. The three-dimensional shape reproduction unit expresses the object by a dynamic equation, applies force from the feature extraction coordinates to the dynamic model to cause the dynamic model to change shape and supplement depth data, and to thereby reproduce the three-dimensional shape of the object. To increase the speed of the processing, it is desirable to divide the image data of the object into portions with little changes in shape and perform the processing for reproducing the three-dimensional shape for each mode.
Inventors
- 👤 Peter Tu
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-04 03:59
CPC Classifications
G; G06; G06T; G06T7/00; G06T7/70; G06V; G06V10/00; G06V10/70; G06V10/74; G06V10/75; G06V10/754
Claims Analysis
Total Claims: 8
Claim 1
Independent Claim
157 words
A method for detecting fingers of a human hand, comprising the steps of: reading the hand and outputting image data of the hand in a form of two-dimensional pixel data; detecting edges of the hand on the basis of said pixel data; determining image lines as lines having the greatest number of edge pixels; determining the orientation line of the hand as the line having the average slope and Y intercept of said image lines; searching the pixel data for edge pixels wherein the search is statistically biased in a direction parallel to the orientation line; and clustering edge pixels defining said finger tips; wherein said steps of determining image lines and determining the orientation line include transforming a rectilinear coordinate system of said detected edges into a polar coordinate system, accumulating edge points in the parameter space, and obtaining the highest accumulated values for each of said lines to determine said orientation line of the hand.
Claim 2
Independent Claim
157 words
A method for detecting fingers of a human hand, comprising the steps of: reading the hand and outputting image data of the hand in a form of two-dimensional pixel data; detecting edges of the hand on the basis of said pixel data; determining image lines as lines having the greatest number of edge pixels; determining the orientation line of the hand as the line having the average slope and Y intercept of said image lines; searching the pixel data for edge pixels wherein the search is statistically biased in a direction parallel to the orientation line; and clustering edge pixels defining said finger tips; wherein said steps of determining image lines and determining the orientation line include transforming a rectilinear coordinate system of said detected edges into a polar coordinate system, accumulating edge points in the parameter space, and obtaining the highest accumulated values for each of said lines to determine said orientation line of the hand.
Claim 3
Independent Claim
150 words
A method of detecting fingers of a human hand comprising the steps of: reading the hand and outputting image data of the hand in a form of two-dimensional pixel data; detecting edges of the hand on the basis of said pixel data; determining image lines as lines having greatest number of edge pixels; determining the orientation line of the hand as the line having the average slope and Y intercept of said image lines; searching the pixel data for edge pixels wherein the search is statistically biased in a direction parallel to the orientation line; and clustering edge pixels defining said finger tips; wherein said clustering step includes choosing arbitrary locations in a cluster, assigning the termination pixel of each search to a cluster location of the basis of a least euclidean distance, and determining new cluster locations by computing the centroid of all said pixels assigned to the cluster.
Claim 4
Independent Claim
150 words
A method of detecting fingers of a human hand comprising the steps of: reading the hand and outputting image data of the hand in a form of two-dimensional pixel data; detecting edges of the hand on the basis of said pixel data; determining image lines as lines having greatest number of edge pixels; determining the orientation line of the hand as the line having the average slope and Y intercept of said image lines; searching the pixel data for edge pixels wherein the search is statistically biased in a direction parallel to the orientation line; and clustering edge pixels defining said finger tips; wherein said clustering step includes choosing arbitrary locations in a cluster, assigning the termination pixel of each search to a cluster location of the basis of a least euclidean distance, and determining new cluster locations by computing the centroid of all said pixels assigned to the cluster.
Claim 5
Independent Claim
156 words
A method of extracting features of an object, comprising the steps of: photographing the object and outputting image data of the object in a form of two-dimensional pixel data; detecting edges of the object on the basis of said pixel data; determining image lines as lines having greatest number of edge pixels; determining the orientation line of the hand as the line having the average slope and Y intercept of said image lines; searching the pixel data for edge pixels wherein the search is statistically biased in a direction parallel to the orientation line; and clustering edge pixels defining said finger tips; wherein said steps of determining image lines and the determining the orientation line include transforming a rectilinear coordinate system of said detected edges into a polar coordinate system, accumulating edge points in the parameter space, and obtaining the highest accumulated values for each of said lines to determine said orientation line of the object.
Claim 6
Independent Claim
156 words
A method of extracting features of an object, comprising the steps of: photographing the object and outputting image data of the object in a form of two-dimensional pixel data; detecting edges of the object on the basis of said pixel data; determining image lines as lines having greatest number of edge pixels; determining the orientation line of the hand as the line having the average slope and Y intercept of said image lines; searching the pixel data for edge pixels wherein the search is statistically biased in a direction parallel to the orientation line; and clustering edge pixels defining said finger tips; wherein said steps of determining image lines and the determining the orientation line include transforming a rectilinear coordinate system of said detected edges into a polar coordinate system, accumulating edge points in the parameter space, and obtaining the highest accumulated values for each of said lines to determine said orientation line of the object.
Claim 7
Independent Claim
150 words
A method of extracting features of an object, comprising the steps of: photographing the object and outputting image data of the object in a form of two-dimensional pixel data; detecting edges of the object on the basis of said pixel data; determining image lines as lines having greatest number of edge pixels; determining the orientation line of the hand as the line having the average slope and Y intercept of said image lines; searching the pixel data for edge pixels wherein the search is statistically biased in a direction parallel to the orientation line; and clustering edge pixels defining said finger tips; wherein said clustering step includes choosing arbitrary locations in a cluster, assigning the termination pixel of each search to a cluster location of the basis of a least euclidean distance, and determining new cluster locations by computing the centroid of all of said pixels assigned to the cluster.
Claim 8
Independent Claim
150 words
A method of extracting features of an object, comprising the steps of: photographing the object and outputting image data of the object in a form of two-dimensional pixel data; detecting edges of the object on the basis of said pixel data; determining image lines as lines having greatest number of edge pixels; determining the orientation line of the hand as the line having the average slope and Y intercept of said image lines; searching the pixel data for edge pixels wherein the search is statistically biased in a direction parallel to the orientation line; and clustering edge pixels defining said finger tips; wherein said clustering step includes choosing arbitrary locations in a cluster, assigning the termination pixel of each search to a cluster location of the basis of a least euclidean distance, and determining new cluster locations by computing the centroid of all of said pixels assigned to the cluster.
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) | 1999-08-20 | 2000-02-19 | 2000-08-20 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2003-08-20 | 2004-02-19 | 2004-08-20 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2007-08-20 | 2008-02-19 | 2008-08-20 | $7700.00 | Window Closed / Lapsed |