Shape recognition process
First Claim
1. In a process of recognizing an object by comparing an objective shape representative of said object with a shape model of the object, the process comprising the steps of:
- A) representing a known shape model in a two dimensional plane as a plurality of first nodal points and a plurality of line segments interconnecting respective pairs of said first nodal points, each line segment including a length characteristic and gradient characteristic;
B) establishing standard values for the length and gradient characteristics, respectively, of each line segment;
C) establishing tolerance ranges for the length and gradient characteristics, respectively, of each line segment;
D) representing said object as a plurality of separate objective shapes each comprised of a row of dots disposed on a two-dimensional plane and having the same number of nodal points as said shape model, said row comprised of a plurality of second nodal points and a plurality of dot segments interconnecting respective pairs of said second nodal points,E) separately evaluating each objective shape determined from step D by;
E1) determining an average spacing of all dots of said dot row from said line segments of said shape model,E2) comparing lengths of said dot segments to said tolerance ranges of respective line segment lengths, to determine a length deviation of each dot segment outside of said tolerance range therefor, and summing said length deviations of all dot segments to establish a length deviation sum,E3) comparing gradients of said dot segments to said tolerance ranges of respective line segment gradients, to determine a gradient deviation of each dot segment outside of said tolerance range therefor, and summing said gradient deviations of all dot segments to establish a gradient deviation sum,E4) summing values of said average spacing, said length deviation sum, and said gradient deviation sum for defining a deviation quantity total, andE5) selecting the objective shape having a lowest deviation quantity total for comparison with the shape model.
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Accused Products
Abstract
The identity of an object is determined by obtaining an image of the objective shape (e.g., by a camera), obtaining from that image an optimum objective shape representative of the object, and comparing the optimum objective shape with a known shape model of the object. The shape model is represented as a plurality of nodal points interconnected by line segments. The optimum objective shape is selected from a number of objective shapes each comprised of a row of dots having the same number of nodal points as the shape model. Each objective shape is compared with the shape model on the basis of (i) the proximity of the dots of the objective shape to the line segments of the shape model, (ii) the length of the dot segments with respect to the lengths of respective line segments, and (iii) the inclinations of the dot segments with respect to the inclinations of the line segments. The objective shape having the closest similarity to (i.e. smallest deviation from) the shape model is selected as the optimum objective shape to be compared with the shape model for identifying the object.
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Citations
36 Claims
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1. In a process of recognizing an object by comparing an objective shape representative of said object with a shape model of the object, the process comprising the steps of:
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A) representing a known shape model in a two dimensional plane as a plurality of first nodal points and a plurality of line segments interconnecting respective pairs of said first nodal points, each line segment including a length characteristic and gradient characteristic; B) establishing standard values for the length and gradient characteristics, respectively, of each line segment; C) establishing tolerance ranges for the length and gradient characteristics, respectively, of each line segment; D) representing said object as a plurality of separate objective shapes each comprised of a row of dots disposed on a two-dimensional plane and having the same number of nodal points as said shape model, said row comprised of a plurality of second nodal points and a plurality of dot segments interconnecting respective pairs of said second nodal points, E) separately evaluating each objective shape determined from step D by; E1) determining an average spacing of all dots of said dot row from said line segments of said shape model, E2) comparing lengths of said dot segments to said tolerance ranges of respective line segment lengths, to determine a length deviation of each dot segment outside of said tolerance range therefor, and summing said length deviations of all dot segments to establish a length deviation sum, E3) comparing gradients of said dot segments to said tolerance ranges of respective line segment gradients, to determine a gradient deviation of each dot segment outside of said tolerance range therefor, and summing said gradient deviations of all dot segments to establish a gradient deviation sum, E4) summing values of said average spacing, said length deviation sum, and said gradient deviation sum for defining a deviation quantity total, and E5) selecting the objective shape having a lowest deviation quantity total for comparison with the shape model. - View Dependent Claims (3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35)
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2. In a process of recognizing an object by comparing an objective shape representative of said object with a shape model of the object, the process comprising the steps of:
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A) representing a known shape model in a two dimensional plane as a plurality of first nodal points and a plurality of line segments interconnecting respective pairs of said first nodal points, each line segment including a length characteristic and gradient characteristic; B) establishing standard values for the length and gradient characteristics, respectively, of each line segment; C) establishing tolerance ranges for the length and gradient characteristics, respectively, of each line segment; D) representing said object as a plurality of separate objective shapes each comprised of a row of dots disposed on a two-dimensional plane and having the same number of nodal points as said shape model, said row comprised of a plurality of second nodal points and a plurality of dot segments interconnecting respective pairs of said second nodal points, E) separately evaluating each objective shape determined from step D by; E1) determining an average spacing of all dots of said dot row from said line segments of said shape model, E2) comparing lengths of said dot segments to said standard values therefor, to determine a length deviation of each dot segment outside of said standard values, and summing said length deviations of all dot segments to establish a length deviation sum, E3) comparing gradients of said dot segments to said standard values therefor, to determine a gradient deviation of each dot segment outside of such standard values, and summing said gradient deviations of all dot segments to determine a gradient deviation sum, E4) summing values of said average spacing, said length deviation sum, and said gradient deviation sum for defining a deviation quantity total, and F) selecting the objective shape having the lowest deviation quantity total for comparison with the shape model determined from step E4. - View Dependent Claims (4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36)
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Specification