Methods for processing color image data employing a chroma, hue, and intensity color representation
First Claim
1. A machine vision method comprising:
- sensing light energy associated with a scene, wherein the sensing step comprises measuring three primary color values, wherein the three primary color values are red, green, and blue, wherein the red value is denoted r, the green value denoted g, and the blue value denoted b;
generating color image data representing at least a portion of the scene, wherein the data are arranged as pixels, and the data for a given pixel comprise an intensity value, a hue value, and a chroma value, the intensity value representing the total sensed light energy associated with the pixel, the hue value representing a dominant or average frequency of the light energy associated with the pixel, and the chroma value representing a measure of the light energy on a side of the visible spectrum complementary to the hue, wherein the generating step comprises converting the three primary color values for the given pixel to a set of values comprising the chroma value, the hue value, and the intensity value, and the converting step comprises determining the intensity value (I) in at least approximate accordance with the relation;
I=√
{square root over (r2+g2+b2)}; and
rendering said color image data, wherein the converting step further comprises;
determining a quantity (β
) in at least approximate accordance with the relation;
determining the hue value (H) in at least approximate accordance with the relation;
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Abstract
A method senses electromagnetic energy associated with a source over an area in N frequency bands and generates color image data representing at least a portion of the area. The data are arranged as pixels, and the data for a given pixel comprise chroma, hue, and intensity values. The N frequency bands constitute a mathematical basis in N-dimensional space, and one band establishes a first reference vector in the space. Equal parts of all bands establish a second reference vector. A reference plane contains the first and second reference vectors. The data for the pixel correspond to a point in the space, and that point and the second reference vector define a plane of interest. Hue is an angle between the reference plane and the plane of interest. Chroma is an angle between the point and the second reference vector. Intensity is the point'"'"'s Euclidean norm.
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Citations
57 Claims
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1. A machine vision method comprising:
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sensing light energy associated with a scene, wherein the sensing step comprises measuring three primary color values, wherein the three primary color values are red, green, and blue, wherein the red value is denoted r, the green value denoted g, and the blue value denoted b; generating color image data representing at least a portion of the scene, wherein the data are arranged as pixels, and the data for a given pixel comprise an intensity value, a hue value, and a chroma value, the intensity value representing the total sensed light energy associated with the pixel, the hue value representing a dominant or average frequency of the light energy associated with the pixel, and the chroma value representing a measure of the light energy on a side of the visible spectrum complementary to the hue, wherein the generating step comprises converting the three primary color values for the given pixel to a set of values comprising the chroma value, the hue value, and the intensity value, and the converting step comprises determining the intensity value (I) in at least approximate accordance with the relation;
I=√
{square root over (r2+g2+b2)}; and
rendering said color image data, wherein the converting step further comprises;determining a quantity (β
) in at least approximate accordance with the relation;determining the hue value (H) in at least approximate accordance with the relation; - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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7. The method of claim 6, wherein one or more of the determining steps is accomplished by table look-up.
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8. The method of claim 1 further comprising:
processing the generated color image data.
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9. The method of claim 8 further comprising:
after the processing step, converting the chroma, hue, and intensity values to red, green, and blue values.
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10. The method of claim 9, wherein the converting step comprises:
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determining quantities β
, σ
, and η
in at least approximate accordance with the relations;determining the red value (r) in at least approximate accordance with the relation; determining the blue value (b) in at least approximate accordance with the relation; determining the green value (q) in at least approximate accordance with one or more of the relations;
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11. The method of claim 10 further comprising:
determining whether to add or subtract the square root in the relation defining the blue value and the green value, based on the hue value.
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12. The method of claim 10, wherein one or more of the determining steps is accomplished by table look-up.
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13. The method of claim 10 further comprising:
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determining whether the chroma value is legal; and based on the determining step, conditionally performing the converting step.
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14. A method comprising:
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sensing electromagnetic energy associated with a source over an area in N frequency bands, wherein N>
1;generating color image data representing at least a portion of the area, wherein the data are arranged as pixels, and the color data for a given pixel comprise an intensity value, a hue value, and a chroma value, wherein the N frequency bands constitute a mathematical basis in N-dimensional space;
wherein one of the N frequency bands establishes a first reference vector in the space, and equal parts of all N frequency bands establish a second reference vector in the space;
wherein a plane containing the first reference vector and the second reference vector establish a reference plane in the space;
wherein the data for the given pixel corresponds to a point in the N-dimensional space, such that the point corresponding to the data for the given pixel and the second reference vector define a plane of interest, such that the hue value is an angle between the reference plane and the plane of interest, and the chroma value is an angle subtended in the plane of interest between the point corresponding to the data for the given pixel and the second reference vector, and the intensity value is a Euclidean norm of the point corresponding to the data for the given pixel in the space; andrendering an image based on said color image data. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27)
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28. A color image data processing method comprising:
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obtaining color image data representing at least a portion of the area from which electromagnetic energy emanates in at least N frequency bands, wherein the data are arranged as pixels, and the color data for a given pixel comprise an intensity value, a hue value, and a chroma value, wherein the frequency bands constitute a mathematical basis in N-dimensional space;
wherein one of the N frequency bands establishes a first reference vector in the space, and equal parts of all N frequency bands establish a second reference vector in the space;
wherein a plane containing the first reference vector and the second reference vector establish a reference plane in the space;
wherein the data for the given pixel corresponds to a point in the N-dimensional space, such that the point corresponding to the data for the given pixel and the second reference vector define a plane of interest, such that the hue value is an angle between the reference plane and the plane of interest, and the chroma value is an angle subtended in the plane of interest between the point corresponding to the data for the given pixel and the second reference vector, and the intensity value is a Euclidean norm of the point corresponding to the data for the given pixel in the space;processing one or more of the chroma, hue, and intensity values; and rendering an image based on said color image data. - View Dependent Claims (29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42)
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43. A computer-readable medium on which is embedded computer software, the software performing a method for generating color image date representing at least a portion of an area from which electromagnetic energy emanates, the method comprising:
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generating color image data representing at least a portion of the area, wherein the data are arranged as pixels, and the color data for a given pixel comprise an intensity value, a hue value, and a chroma value, wherein the N frequency bands constitute a mathematical basis in N-dimensional space;
wherein one of the N frequency bands establishes a first reference vector in the space, and equal parts of all N frequency bands establish a second reference vector in the space;
wherein a plane containing the first reference vector and the second reference vector establish a reference plane in the space;
wherein the data for the given pixel corresponds to a point in the N-dimensional space, such that the point corresponding to the data for the given pixel and the second reference vector define a plane of interest, such that the hue value is an angle between the reference plane and the plane of interest, and the chroma value is an angle subtended in the plane of interest between the point corresponding to the data for the given pixel and the second reference vector, and the intensity value is a Euclidean norm of the point corresponding to the data for the given pixel in the space; andrendering an image based on said color image data.
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44. A machine vision method comprising:
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sensing light energy associated with a scene; generating color image data representing at least a portion of the scene, wherein the data are arranged as pixels, and the data for a given pixel comprise an intensity value, a hue value, and a chroma value, the intensity value representing the total sensed light energy associated with the pixel, the hue value representing a dominant or average frequency of the light energy associated with the pixel, and the chroma value representing a measure of the light energy on a side of the visible spectrum complementary to the hue processing the generated color image data; after the processing step, converting the chroma, hue, and intensity values to red, green, and blue values, wherein the converting step comprises; determining quantities β
, σ
, and η
in at least approximate accordance with the relations;determining the red value (r) in at least approximate accordance with the relation; determining the blue value (b) in at least approximate accordance with the relation; determining the green value (g) in at least approximate accordance with one or more of the relations; rendering said color image data. - View Dependent Claims (45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57)
determining the hue value (H) in at least approximate accordance with the relation;
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52. The method of claim 51, wherein one or more of the determining steps is accomplished by table look-up.
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53. The method of claim 50, wherein the converting step further comprises:
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determining the chroma value (C) in at least approximate accordance with the relation;
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54. The method of claim 53, wherein one or more of the determining steps is accomplished by table look-up.
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55. The method of claim 44, further comprising:
determining whether to add or subtract the square root in the relation defining the blue value and the green value, based on the hue value.
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56. The method of claim 44, wherein one or more of the determining steps is accomplished by table look-up.
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57. The method of claim 44, further comprising:
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determining whether the chroma value is legal; and based on the determining step, conditionally performing the converting step.
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Specification