Method for electronic color matching

• US 8,743,137 B2
• Filed: 04/10/2007
• Issued: 06/03/2014
• Est. Priority Date: 04/10/2006
• Status: Active Grant

• Current Assignee: Syndigo, LLC
• Original Assignee: Edgenet, Inc. (Syndigo, LLC)
• Inventors: Peters, Sean, Rudolph, Ron
• Primary Examiner(s): Xiao, Ke
• Assistant Examiner(s): CRADDOCK, ROBERT J
• Application Number:
  US11/733,729
• Publication Number:
  US 20070242877A1
• Time in Patent Office: 2,611 Days
• Field of Search: 345/593, 345/604, 345/589, 711/203
• US Class Current: 345/593
• CPC Class Codes: G01J 3/46 Measurement of colour; Colour measuring devices, e.g. colorimeters measuring colour temperature G01J5/60
• CPC Class Codes: G01J 3/463 Colour matching
• CPC Class Codes: G01J 3/52 using colour charts
• CPC Class Codes: G06V 10/75 Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries

Abstract

Disclosed is a method to define automatically, in a pre-selected color space, at least one user-provided sample color. The method includes defining at least one target color within the color space to yield a standard color data set and providing a physical color swatch corresponding to the defined target color. The user then provides a digitized image comprising the user-provided sample color juxtaposed with the physical color swatch, to yield a sample color data set. The sample color data set is then compared to the standard color data set by means of a program stored on a programmable computer to determine a set of coordinates within the color space that defines the user-provided sample color.

Claims

1. A method to define automatically, in a pre-selected color space, at least one user-provided sample color, the method comprising:

(a) defining mathematically within a programmable computer each of a plurality of target colors with coordinates within the color space to yield a standard color data set;

(b) providing a multi-chromatic physical color swatch comprising a plurality of swatch colors spanning at least a portion of the color space, wherein each of the plurality of swatch colors corresponds to one of the plurality of target colors defined in step (a) by being defined within the color space with the coordinates defining the one of the plurality of target colors;

(c) digitally imaging a plurality of user-provided sample colors juxtaposed with the multi-chromatic physical color swatch to provide a plurality of digitally imaged user-provided sample colors juxtaposed to a digitally imaged plurality of swatch colors, thereby yielding a sample color data set comprising coordinates within the color space defining the digitally imaged user-provided sample colors and each of the digitally imaged plurality of swatch colors; and

then

(d) comparing the coordinates in the sample color data set of step (c) with the coordinates in the standard color data set of step (a) by means of a program comprising a clustering algorithm stored on the programmable computer to thereby determine coordinates within the color space that defines at least one of the user-provided sample colors, wherein the clustering algorithm clusters the plurality of digitally imaged user-provided sample colors into a predefined number of representative colors, and wherein the comparing comprises comparing coordinates defining each of the representative colors against the coordinates defining each of the target colors in the standard color data set.

2. The method of claim 1, wherein the physical color swatch comprises a physical array and the physical array comprises:

a hole therein, and wherein the digitally imaging in step (c) comprises placing the physical array on an item comprising the user-provided sample color such that the user-provided sample color is visible through the hole; and

digitally imaging the physical array with the user-provided sample color visible through the hole in the physical array.

3. The method of claim 1, wherein the digitally imaging in step (c) comprises photographing the physical color swatch in juxtaposition with the user-provided sample color.

4. The method of claim 3, wherein the plurality of swatch colors in the physical color swatch span a dynamic range of a camera used in the photographing.

5. The method of claim 1, wherein in step (d), the clustering algorithm is a fuzzy c-means clustering algorithm.

6. The method of claim 1, wherein step (d) comprises:

transforming the sample color data set of step (c) with respect to the standard color data set of step (a) to yield a transformed sample color data set, and then clustering the digitally imaged user-provided sample colors in the transformed sample color data set into the pre-determined number of representative colors; and

determining a minimum mathematical distance between coordinates in the standard color data set and coordinates defining a transformed user-provided sample color in the transformed and clustered sample color data set, wherein the minimum mathematical distance determines the coordinates within the color space that defines the at least one user-provided sample color.

7. The method of claim 6, wherein the minimum mathematical distance is determined using a metric selected from a Euclidean metric, a taxicab metric, or a Chebyshev metric.

8. The method of claim 1, wherein the plurality of swatch colors in the physical color swatch are spread evenly across an entire spectrum of visible colors.

9. The method of claim 1, wherein the providing the physical color swatch in step (b) comprises providing a plurality of physical arrays, wherein each of the plurality of the physical arrays comprises an identifier, and wherein a subset of the identifiers links a subset of the plurality of the physical arrays to the standard color data set of step (a).

10. A method to define automatically, in a pre-selected color space, at least one user-provided sample color, the method comprising:

(a) defining mathematically within a programmable computer each of a plurality of target colors with coordinates within the color space to yield a standard color data set;

(b) providing a multi-chromatic physical color swatch comprising a plurality of swatch colors spanning at least a portion of the color space, wherein each of the plurality of swatch colors corresponds to one of the plurality of target colors defined in step (a) by being defined within the color space with the coordinates defining the one of the plurality of target colors;

(c) digitally imaging a plurality of user-provided sample colors juxtaposed with the multi-chromatic physical color swatch to provide a plurality of digitally imaged user-provided sample colors juxtaposed to a digitally imaged plurality of swatch colors, thereby yielding a sample color data set comprising coordinates within the color space defining the digitally imaged user-provided sample color and each of the digitally imaged plurality of swatch colors; and

then

(d) comparing the coordinates in the sample color data set of step (c) with the coordinates in the standard color data set of step (a) by means of a program comprising a clustering algorithm stored on the programmable computer to thereby determine coordinates within the color space that defines at least one of the user-provided sample colors, wherein the clustering algorithm clusters the plurality of digitally imaged user-provided sample colors into a predefined number of representative colors, and wherein the comparing comprises pairing coordinates defining each of the representative colors with the coordinates in the standard color data set in every possible manner and determining a distance measure for each pairing.

11. The method of claim 10, wherein the physical color swatch comprises a physical array and the physical array comprises:

a hole therein, and wherein the digitally imaging in step (c) comprises placing the physical array on an item comprising the user-provided sample color such that the user-provided sample color is visible through the hole; and

digitally imaging the physical array with the user-provided sample color visible through the hole in the physical array.

12. The method of claim 10, wherein the digitally imaging in step (c) comprises photographing the physical color swatch in juxtaposition with the user-provided sample color.

13. The method of claim 12, wherein the plurality of swatch colors in the physical color swatch span a dynamic range of a camera used in the photographing.

14. The method of claim 10, wherein in step (d), the clustering algorithm is a fuzzy c-means clustering algorithm.

15. The method of claim 10, wherein step (d) comprises:

transforming the sample color data set of step (c) with respect to the standard color data set of step (a) to yield a transformed sample color data set, and then clustering the digitally imaged user-provided sample colors in the transformed sample color data set into the pre-determined number of representative colors; and

determining a minimum mathematical distance between coordinates in the standard color data set and coordinates defining a transformed user-provided sample color in the transformed and clustered sample color data set, wherein the minimum mathematical distance determines the coordinates within the color space that defines the at least one user-provided sample color.

16. The method of claim 15, wherein the minimum mathematical distance is determined using a metric selected from a Euclidean metric, a taxicab metric, or a Chebyshev metric.

17. The method of claim 10, wherein the plurality of swatch colors in the physical color swatch are spread evenly across an entire spectrum of visible colors.

18. The method of claim 10, wherein the providing the physical color swatch in step (b) comprises providing a plurality of physical arrays, wherein each of the plurality of the physical arrays comprises an identifier, and wherein a subset of the identifiers links a subset of the plurality of the physical arrays to the standard color data set of step (a).