Compact color feature vector representation
First Claim
1. A computer-program product, tangibly stored on machine-readable medium, the product comprising instructions to cause a computer to:
- retrieve images from an image data store;
generate a global color table for the image data store;
for each of a plurality of original images in the image data store, estimate an estimated number of distinct colors in an original image, use the estimated number to determine a number N of colors to use to represent the original image as a quantized image, map each of the quantized image colors to a resultant color in the global color table, and generate a color feature vector of color descriptors to represent the image;
receive a query comprising a query image;
use the query image to create a query color feature vector of one or more descriptors, each descriptor comprising a color index that references a location of a color in the global color table; and
compare the query color feature vector to the color feature vectors of the plurality of images to identify images among the plurality of images that satisfy the query.
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Accused Products
Abstract
Methods and apparatus for representing images using a compact color feature vector. A color feature vector includes a color element for each color in an image-specific set of colors. A color element includes a color identifier and a relative color occurrence. A compact color feature vector may be used in a content-based image retrieval (CBIR) system. The CBIR system includes an image data store containing multiple images. A color feature vector data store includes a variable-length color feature vector for each image in the image data store. A computer program receives a query and uses the variable-length color feature vectors in the color feature vector data store to identify which images satisfy the query.
26 Citations
18 Claims
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1. A computer-program product, tangibly stored on machine-readable medium, the product comprising instructions to cause a computer to:
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retrieve images from an image data store; generate a global color table for the image data store; for each of a plurality of original images in the image data store, estimate an estimated number of distinct colors in an original image, use the estimated number to determine a number N of colors to use to represent the original image as a quantized image, map each of the quantized image colors to a resultant color in the global color table, and generate a color feature vector of color descriptors to represent the image; receive a query comprising a query image; use the query image to create a query color feature vector of one or more descriptors, each descriptor comprising a color index that references a location of a color in the global color table; and compare the query color feature vector to the color feature vectors of the plurality of images to identify images among the plurality of images that satisfy the query. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A system comprising:
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an image data store containing a plurality of images; a global color table for the image data store; and a computer program comprising instructions operable to; for each of a plurality of original images in the image data store, estimate an estimated number of distinct colors in an original image, use the estimated number to determine a number N of colors to use to represent the original image as a quantized image, map each of the quantized image colors to a resultant color in the global color table, and generate a color feature vector of color descriptors to represent the image; receive a query comprising a query image; use the query image to create a query color feature vector of one or more descriptors, each descriptor comprising a color index that references a location of a color in the global color table; and compare the query color feature vector to the color feature vectors of the plurality of images to identify images among the plurality of images that satisfy the query. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A computer-implemented method comprising:
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retrieving images from an image data store; generating a global color table for the image data store; for each of a plurality of original images in the image data store, estimating an estimated number of distinct colors in an original image, use the estimated number to determine a number N of colors to use to represent the original image as a quantized image, mapping each of the quantized image colors to a resultant color in the global color table, and generating a color feature vector of color descriptors to represent the image; receiving a query comprising a query image; using the query image to create a query color feature vector of one or more descriptors, each descriptor comprising a color index that references a location of a color in the global color table; and comparing the query color feature vector to the color feature vectors of the plurality of images to identify images among the plurality of images that satisfy the query. - View Dependent Claims (14, 15, 16, 17, 18)
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Specification