Method for recognition between a first object and a second object each represented by images
AssigneeKee Square S.r.l.
InventorsMarco Marcon, Davide Onofrio
Life of this patent
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Abstract
A method for recognition between a first and second object represented by at least one first image and at least one second image, includes defining rectangular assemblies of random pixels; filtering the first image with first n filters obtained from the assemblies of pixels to obtain n first filtered matrices; classifying the n first filtered matrices by providing a first center and a first radius within a space of N dimensions; filtering the second image with the first n filters to obtain n second filtered matrices; classifying the n second filtered matrices by providing a second center within the space of N dimensions; and comparing the first center and first radius with the second center.
Claims20
A method for recognition between a first object and a second object represented by at least one first image and at least one second image, each containing a plurality of pixels, comprising the following steps:
- defining a plurality of randomly positioned rectangular array of pixels;
- filtering by the mathematical operation of bi-dimensional matrix convolution of said first image with the first n matrices obtained from said randomly positioned rectangular array of pixels to obtain n first filtered matrices;
- classifying said n first filtered matrices by providing a first centre and a first radius within a space of N dimensions, for each of said n first filtered matrices, said first radius and said first centre representing n first hyperspheres within a space of N dimensions;
- filtering by the mathematical operation of bi-dimensional matrix convolution of said second image with the first n matrices obtained from said randomly positioned rectangular array of pixels to obtain n second filtered matrices;
- classifying said n second filtered matrices by providing a second centre within said space of N dimensions, for each of said n second filtered matrices;
- comparing said first centre and said first radius of each of said first filtered matrices with said second centre for each of said n second filtered matrices;
- and
- considering that recognition between said first object and said second object has taken place if at least one said second centre lies at a distance from said first centre which is less than or equal to at least one said first radius,
- wherein an inserted image of an unknown object is recognized only if a vector of the unknown object pertains to an N-dimensional sphere defined by the centre and radius of a previously inserted image.
A method for recognition between a first object and a second object represented by at least one first image and at least one second image, each containing a plurality of pixels, comprising the following steps:
- defining a plurality of randomly positioned rectangular array of pixels;
- filtering by the mathematical operation of bi-dimensional matrix convolution of said first image with the first n matrices obtained from said randomly positioned rectangular array of pixels to obtain n first filtered matrices;
- classifying said n first filtered matrices by providing a first centre and a first radius within a space of N dimensions, for each of said n first filtered matrices, said first radius and said first centre representing n first hyperspheres within a space of N dimensions;
- filtering by the mathematical operation of bi-dimensional matrix convolution of said second image with the first n matrices obtained from said randomly positioned rectangular array of pixels to obtain n second filtered matrices;
- classifying said n second filtered matrices by providing a second centre within said space of N dimensions, for each of said n second filtered matrices;
- comparing said first centre and said first radius of each of said first filtered matrices with said second centre for each of said n second filtered matrices;
- and
- considering that recognition between said first object and said second object has taken place if at least one said second centre lies at a distance from said first centre which is less than or equal to at least one said first radius,
- wherein the steps of classifying said n first and second filtered matrices takes place by using a RBF (radial basis function) neural network, and a distance of a vector from a centre of a closest neuron of said neural network is evaluated by rule L1:
- d
- L
-
-
- 1
- =
- ∑
- i
- =
- 1
- N
-
-
-
- Vi
- -
- Pi
-
- where V and P are two vectors, and I is an index which traverses the N space dimensions.
Dependencies are inferred from the claim text.