Mars, Incorporated

Mei, Inc.

Gaston Baudat

Fatiha Anouar

Christian Voser

Gregory John Billington

Didier Rossel

Bob MacKenzie

Carl Alexander Phillips

A method of deriving a classifier for classifying items using a plurality of variables for characteristics of the items, the method comprising determining a representative subset of the variables for use in said classifier.

Classification using support vector machines and variables selection

A method of testing a document comprises deriving a plurality of measurements from the document at a resolution R and processing the measurements to derive values at a different resolution.

Method and apparatus for processing signals in testing currency items

A method of deriving a function for classifying items of currency. The method comprises processing training data vectors corresponding to features of a plurality of currency items, and derives a support vector machine classification function involving a plurality of support vectors.

Currency validator

Processing data derived from currency items includes measuring samples of currency items of classes to produce feature vectors in a first space and mapping the feature vectors to a second space in which there is a clearer separation of the classes.

Classification method and apparatus

A method of classifying an item of currency using a currency tester comprises sensing variable characteristics of a currency item and deriving a data vector (X) using values of the sensed characteristics, and transforming the data vector so that the variables represented by at least first and second sets of components (Y, Y) of the transformed vector are substantially independent, so that the mahalanobis distance of X is substantially equivalent to the sum of the mahalanobis distances of the components (Y, Y), and calculating a mahalanobis distance in at least two parts using said first and second sets of components.

A method and apparatus for securing communications in a currency-handling machine. The method includes generating an encrypted transaction message based on a bill acceptor transaction event, communicating the encrypted transaction message to a transaction controller, decrypting the encrypted transaction message and enabling the bill acceptor to accept bills.

Secure communications for a currency handling machine

A method of deriving a classifying function for classifying items of currency includes deriving a plurality of measurements from at least one currency sensor and a plurality of currency items, and forming a set of data from the measurements, the elements of the data set corresponding to points in a first space, and determining a set of values corresponding to the measured values. The method also includes selecting a kernel function corresponding to a mapping of the first space to a second space, the method including deriving an expression representing the function of the measured values in terms of the kernel function and using it to derive a classifying function.

Money validator

Method and apparatus for the classification of an article

For the classification of a pattern in particular on a banknote or a coin, a receiving system detects, by a measurement procedure, vectors of a test item, a pre-processing system transforms the measured vectors into local feature vectors ALCi(l) and a learning classification system carries out a plurality of testing operations. A first activity compares in a first testing operation each of the local feature vectors ALCi(l) to a vectorial reference value. It is only if the first testing operation takes place successfully that the first activity, by means of first estimates which are stored in a data base, links the local feature vectors ALC(l) to provide global line feature vectors AGIi. In a second testing operation a third activity compares the global line feature vectors AGIi to corresponding reference values and, if the second testing operation is successful, computes a single global surface vector AGF of which a fourth activity. in a third testing operation, compares its distance in accordance with Mahalanobis relative to an estimated surface vector to a reference value. The test item is reliably classified if all three testing operations take place successfully.

Method for the classification of a pattern, for example on a banknote or

For the classification of a pattern in particular on a banknote or a coin, a receiving system detects, by a measurement procedure, vectors of a test item, a pre-processing system transforms the measured vectors into local feature vectors ALCi(l) and a learning classification system carries out a plurality of testing operations. A first activity compares in a first testing operation each of the local feature vectors ALCi(l) to a vectorial reference value. It is only if the first testing operation takes place successfully that the first activity, by means of first estimates which are stored in a data base, links the local feature vectors ALC(l) to provided global line feature vectors AGIi. In a second testing operation a third activity compares the global line feature vectors AGIi to corresponding reference values and, if the second testing operation is successful, computes a single global surface vector AGF of which a fourth activity, in a third testing operation, compares its distance in accordance with Mahalanobis relative to an estimated surface vector to a reference value. The test item is reliably clasified if all three testing operations take place successfully.

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Geneva, Switzerland

Gaston Baudat