Computer based method and apparatus for object recognition

Claim 1

A method for recognizing an image of an object, comprising: a) extracting a singular value (SV) feature vector from said image of an object; b) determining dimensions of said image of said object; c) creating a first essential singular value vector (ESV) based upon said extracted singular value (SV) feature vector and said dimensions of said image of said object; d) comparing said first ESV vector of said image of an object to be recognized with a second ESV vector stored in a database, where said second ESV vector is representative of a known object to determine a distance between said first ESV vector and said second ESV vector; and, e) determining if said distance is within a predetermined range, which would indicate that said object to be recognized is the same as said known object represented by said second ESV vector.

Claim 2

A method for recognizing an image of an object, comprising: a) extracting a singular value (SV) feature vector from said image of an object; b) determining dimensions of said image of said object; c) creating a first essential singular value vector (ESV) based upon said extracted singular value (SV) feature vector and said dimensions of said image of said object; d) comparing said first ESV vector of said image of an object to be recognized with a second ESV vector stored in a database, where said second ESV vector is representative of a known object to determine a distance between said first ESV vector and said second ESV vector; and, e) determining if said distance is within a predetermined range, which would indicate that said object to be recognized is the same as said known object represented by said second ESV vector.

Claim 5

A method for recognizing an image of an object, comprising: a) extracting a singular value (SV) feature vector from said image of an object; b) determining dimensions of said image of said object; c) creating a first essential singular value vector (ESV) based upon said extracted singular value (SV) feature vector and said dimensions of said image of said object; d) comparing said first ESV vector of said image of said object to be recognized with a second ESV vector stored in a database, where said second ESV vector is representative of a first known object to determine a first distance between said first ESV vector and said second ESV vector; e) comparing said first ESV vector of said image of said object to be recognized with a third ESV vector stored in a database, where said third ESV vector is representative of a second known object to determine a second distance between said first ESV vector and said third ESV vector; and, f) comparing said first and second distances to determine which of said first and second distances is lower where said lower distance indicates which of said second and third ESV vectors is more likely to represent the object to be recognized.

Claim 6

A method for recognizing an image of an object, comprising: a) extracting a singular value (SV) feature vector from said image of an object; b) determining dimensions of said image of said object; c) creating a first essential singular value vector (ESV) based upon said extracted singular value (SV) feature vector and said dimensions of said image of said object; d) comparing said first ESV vector of said image of said object to be recognized with a second ESV vector stored in a database, where said second ESV vector is representative of a first known object to determine a first distance between said first ESV vector and said second ESV vector; e) comparing said first ESV vector of said image of said object to be recognized with a third ESV vector stored in a database, where said third ESV vector is representative of a second known object to determine a second distance between said first ESV vector and said third ESV vector; and, f) comparing said first and second distances to determine which of said first and second distances is lower where said lower distance indicates which of said second and third ESV vectors is more likely to represent the object to be recognized.

Claim 12

A method for recognizing an image of an object, comprising: a) extracting a singular value (SV) feature vector from said image of an object; b) determining dimensions of said image of said object; c) creating a first essential singular value vector (ESV) based upon said extracted singular value (SV) feature vector and said dimensions of said image of said object; d) comparing said first ESV vector of said image of said object to be recognized with a plurality of ESV vectors stored in a database, where each of said stored ESV vectors is representative of a known object to determine a distance between said first ESV vector and each of said plurality of ESV vectors; and, e) selecting an ESV vector from said plurality of ESV vectors having the lowest distance to said first ESV vector, where the ESV vector corresponding to said lowest distance is likely to represent the object to be recognized.

Claim 13

A method for recognizing an image of an object, comprising: a) extracting a singular value (SV) feature vector from said image of an object; b) determining dimensions of said image of said object; c) creating a first essential singular value vector (ESV) based upon said extracted singular value (SV) feature vector and said dimensions of said image of said object; d) comparing said first ESV vector of said image of said object to be recognized with a plurality of ESV vectors stored in a database, where each of said stored ESV vectors is representative of a known object to determine a distance between said first ESV vector and each of said plurality of ESV vectors; and, e) selecting an ESV vector from said plurality of ESV vectors having the lowest distance to said first ESV vector, where the ESV vector corresponding to said lowest distance is likely to represent the object to be recognized.

Claim 16

A method of identifying an object within an image containing two or more objects, comprising: a) detecting one or more candidate class(es) of objects within said image based upon a segmentation of said image; b) selecting a specific candidate class of objects to be recognized based upon a user specification; c) recognizing a sub-image of an object within said specific candidate class of objects, where said recognizing is accomplished by steps comprising the following: 1) extracting a singular value (SV) feature vector from said sub-image of said object to be recognized; 2) determining dimensions of said sub-image of said object to be recognized; 3) creating a first essential singular value vector (ESV) based upon said extracted SV feature vector and said dimensions of said sub-image of said object to be recognized; 4) comparing said first ESV vector of said sub-image of said object to be recognized with a second ESV vector stored in a database, where said second ESV vector is representative of a known object to determine a distance between said first ESV vector and said second ESV vector; and, 5) determining if said distance is within a predetermined range, which would indicate that said object to be recognized is identified as said known object represented by said second ESV vector.

Claim 17

A method of identifying an object within an image containing two or more objects, comprising: a) detecting one or more candidate class(es) of objects within said image based upon a segmentation of said image; b) selecting a specific candidate class of objects to be recognized based upon a user specification; c) recognizing a sub-image of an object within said specific candidate class of objects, where said recognizing is accomplished by steps comprising the following: 1) extracting a singular value (SV) feature vector from said sub-image of said object to be recognized; 2) determining dimensions of said sub-image of said object to be recognized; 3) creating a first essential singular value vector (ESV) based upon said extracted SV feature vector and said dimensions of said sub-image of said object to be recognized; 4) comparing said first ESV vector of said sub-image of said object to be recognized with a second ESV vector stored in a database, where said second ESV vector is representative of a known object to determine a distance between said first ESV vector and said second ESV vector; and, 5) determining if said distance is within a predetermined range, which would indicate that said object to be recognized is identified as said known object represented by said second ESV vector.

Claim 23

A method of organizing a first database containing representations of one or more images, where each image is associated with an object, comprising: a) extracting a singular value (SV) feature vector from each of said one or more images; b) determining dimensions of each of said one or more images; c) creating an essential singular value vector (ESV) based upon said extracted singular value (SV) feature vector and said dimensions of each of said one or more images; and, d) calculating an essential collection matrix from said ESV of each of said one or more images, where said essential collection matrix represents an image of an identical object.

Claim 24

A method of organizing a first database containing representations of one or more images, where each image is associated with an object, comprising: a) extracting a singular value (SV) feature vector from each of said one or more images; b) determining dimensions of each of said one or more images; c) creating an essential singular value vector (ESV) based upon said extracted singular value (SV) feature vector and said dimensions of each of said one or more images; and, d) calculating an essential collection matrix from said ESV of each of said one or more images, where said essential collection matrix represents an image of an identical object.