Image identification system
First Claim
1. A method for comparing a first image to a second image, the method comprising:
- deriving a first image data set based on the first image and a second image data set based on the second image, wherein the first and second image data sets include a plurality of data elements and are model representations of the first and second images;
comparing at least one data element in the first image data set with at least one data element in the second image data set, wherein comparing comprises generating a first count of the plurality of data elements in the first image data set that approximately match the plurality of data elements in the second image data set;
re-positioning at least one of the first and second image data sets and the plurality of data elements associated therewith; and
generating a second count of the plurality of data elements in the first image data set that approximately match the plurality of data elements in the second image data set.
1 Assignment
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Accused Products
Abstract
Methods and procedures for improving the performance and reliability of image analysis within an image identification system include a series of image qualification functions designed to quickly process a fraction of available image data and to provide feedback to a system user pertaining to image quality and authenticity. Functions designed to produce image models based on original image data and to catalogue such image models into a searchable database are included in the present invention. The present invention also includes functions for comparing one image model to another. Finally, the present invention provides functions for making a quick determination as to which, if any, of a potential thousands (or more, i.e., millions) of image models within a searchable database exhibit a desired level of similarity, as compared to a target image model.
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Citations
39 Claims
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1. A method for comparing a first image to a second image, the method comprising:
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deriving a first image data set based on the first image and a second image data set based on the second image, wherein the first and second image data sets include a plurality of data elements and are model representations of the first and second images;
comparing at least one data element in the first image data set with at least one data element in the second image data set, wherein comparing comprises generating a first count of the plurality of data elements in the first image data set that approximately match the plurality of data elements in the second image data set;
re-positioning at least one of the first and second image data sets and the plurality of data elements associated therewith; and
generating a second count of the plurality of data elements in the first image data set that approximately match the plurality of data elements in the second image data set. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method for comparing a first image data set to a second image data set, wherein the first and second image data sets are derived from fingerprint images and include a plurality of data elements comprising at least one of bifurcation representations, rod representations, vector segments associated with bifurcation representations, vector segments associated with rod representations, vector segments not associated with bifurcation representations, vector segments not associated with rod representations, microminutia points, and combinations thereof, the method comprising:
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re-positioning at least one of the first and second image data sets, thereby re-positioning the set of data elements associated therewith;
generating a count of the data elements in the first image data set that approximately match the data elements in the second image data set; and
repeating said re-positioning and said generating a count until a maximum comparison point is identified, said maximum comparison point being a point at which said count approximates a maximum value. - View Dependent Claims (12, 13, 14, 15, 16, 17)
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18. A method for efficiently and accurately comparing a first image to a plurality of other images, wherein the first and second images are fingerprint images, the method comprising:
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deriving a first image data set based on the first image and a plurality of other image data sets based on the plurality of other images, wherein each image data set includes a plurality of data elements and is a model representation of a corresponding image, and wherein the plurality of data elements are selected from a group consisting of bifurcation representations, rod representations, vector segments associated with bifurcation representations, vector segments associated with rod representations, vector segments not associated with bifurcation representations, vector segments not associated with rod representations, microminutia points, and combinations tnereof; and
comparing at least one data element in the first image data set with data elements in at least one of the plurality of other image data sets.
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19. A method for efficiently and accurately comparing a first image to a plurality of other images, wherein the first and second images are fingerprint images, the method comprising:
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deriving a first image data set based on the first image and a plurality of other image data sets based on the plurality of other images, wherein each image data set includes a plurality of data elements and is a model representation of a corresponding image, and wherein the plurality of data elements are selected from a group consisting of bifurcation representations, rod representations, vector segments associated with bifurcation representations, vector segments associated with rod representations, vector segments not associated with bifurcation representations, vector segments not associated with rod representations, microminutia points, and combinations thereof;
comparing at least one data element in the first image data set with data elements in at least one of the plurality of other image data sets;
generating a count for each of the plurality of other image data sets, wherein generating the count comprises calculating a quantity of data elements in each of the plurality of other image data sets that approximately match data elements taken from the first image data set;
selecting from the plurality of other image data sets a predetermined number of image data sets having the most data elements that approximately match data elements taken from the first image data set; and
performing a more thorough comparison of the predetermined number of image data sets to the first image data set.
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20. A method for efficiently and accurately comparing a first image to a plurality of other images, the method comprising:
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deriving a first image data set based on the first image and a plurality of other image data sets based on the plurality of other images, wherein each image data set includes a plurality of data elements and is a model representation of a corresponding image; and
comparing at least one data element in the first image data set with data elements in at least one of the plurality of other image data sets, wherein comparing comprises creating a B-tree data file for each of a plurality of data element types and categorizing and storing, based on a set of data normalization rules, substantially all of the data elements included in the plurality of other image data sets. - View Dependent Claims (21, 22, 23, 24, 25, 26, 27, 28)
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29. A method for efficiently and accurately comparing a first image to a plurality of other images, the method comprising:
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deriving a first image data set based on the first image and a plurality of other image data sets based on the plurality of other images, wherein each image data set includes a plurality of data elements and is a model representation of a corresponding image; and
comparing at least one data element in the first image data set with data elements in at least one of the plurality of other image data sets, wherein comparing comprises;
creating a directory that progressively lists, based on at least one measured characteristic, a substantial number of a first type of data elements that appear in the plurality of other image data sets, wherein each data element in the directory is listed with an identifier that represents association with a particular image data set within which the data element appears; and
comparing data elements of the first type taken from the first image data set to the data elements that are progressively listed in the directory. - View Dependent Claims (30, 31, 32, 33, 34)
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35. A method for efficiently and accurately comparing a first image data set to a plurality of other image data sets, wherein the first and plurality of other image data sets are individually derived from fingerprint images and include a plurality of data elements of a plurality of types, the plurality of types comprising at least one of bifurcation representations, rod representations, vector segments associated with bifurcation representations, vector segments associated with rod representations, vector segments not associated with bifurcation representations, vector segments not associated with rod representations, microminutia points, and combinations thereof, the method comprising:
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creating a directory that progressively lists, based on at least one measured characteristic, a substantial number of a first type of data elements that appear in the plurality of other image data sets, wherein each data element in the directory includes an identifier that represents association with a particular image data set within which the data element appears;
creating an array having a two-entry cell for each of a range of potential configurations for the first type of data element;
recording in a first entry of at lest one two-entry cell, a quantity value representing a number of consecutive data elements in the directory that demonstrate characteristics that are approximately similar to characteristics of the one of the range of potential configurations for the first type of data element that is associated with the two-entry cell within which the first entry is being recorded;
recording in a second entry of at least one two-entry cell, an index value corresponding to an initial data element that begins the number of consecutive data elements listed in the directory;
identifying a two-entry cell in the array that is associated with a data element configuration having characteristics approximately identical to a target data element of the first type taken from the first image data set; and
comparing the target data element to a group of consecutive data elements listed in the directory, as indicated by the two-entry cell associated with the target data element. - View Dependent Claims (36, 37)
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38. A method for efficiently and accurately comparing a first image data set to a plurality of other image data sets, wherein the first and plurality of other image data sets are individually derived from fingerprint images and include a plurality of data elements of a plurality of types, the plurality of types comprising at least one of bifurcation representations, rod representations, vector segments associated with bifurcation representations, vector segments associated with rod representations, vector segments not associated with bifurcation representations, vector segments not associated with rod representations, microminutia points, and combinations thereof, the method comprising:
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creating a B-tree data file for at least one of the plurality of data element types and categorizing and storing, based on a set of data normalization rules, substantially all of the data elements included in the plurality of other image data sets;
storing each data element in the B-tree data files with an identifier that represents association with a particular image data set within which the data element appears; and
comparing at least one target data element from the first image data set to data elements in the B-tree data file having data elements of a same type as each target data element being compared. - View Dependent Claims (39)
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Specification