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US 5,854,855 AGranted
Method and system using meta-classes and polynomial discriminant functions for handwriting recognition
AssigneeMotorola, Inc.
InventorsJames H. Errico, Nicholas M. Labun, John J. Loda, Michael C. Murdock, Shay-Ping T. Wang
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Abstract
A method and system of identifying text in a handwriting input is provided. The system includes a feature extractor (30) and a classifier (32). The feature extractor (30) extracts a plurality of features from handwriting input. The classifier (32) classifies the handwriting input according to a discriminant function that is based on a polynomial expansion. The text is identified according to the discriminant function output.
Claims33
In a computer, a method of identifying text in a handwriting input, the method comprising the following steps:
- extracting a plurality of features from the handwriting input;
- generating a meta-class signal by distributing the plurality of features to a meta-class classifier for identifying a meta-class comprising a plurality of meta-class characters that are not easily discernible from one another;
- distributing the plurality of features to a plurality of character classifiers for distinguishing between the meta-class characters;
- generating a plurality of character classifier output signals based on a plurality of polynomial discriminant functions, each of the polynomial discriminant functions having a form ##EQU3## wherein x.sub.j represents the plurality of features;
- wherein i, j, m and n are integers;
- wherein y represents one of the character classifier output signals;
- wherein w.sub.i represents a coefficient;
- and wherein g.sub.ji represents an exponent;
- and
- identifying the handwritten text as a function of the meta-class signal and the plurality of character classifier output signals.
7 more elements
In a computer, a method of identifying text in a handwriting input, the method comprising the following steps:
- extracting a plurality of features from a data frame that represent the handwriting input;
- generating a meta-class signal by distributing the plurality of features to a meta-class classifier for identifying a meta-class comprising a plurality of meta-class characters that are not easily discernible from one another;
- distributing the plurality of features to a plurality of meta-class character classifiers trained using localized features to distinguish between the meta-class characters;
- generating a plurality of meta-class character classifier output signals based on a plurality of polynomial discriminant functions
- classifying the plurality of features according to a discriminant function based on a polynomial expansion having a form ##EQU5## wherein x.sub.j represents the plurality of features;
- wherein I, j, m and n are integers;
- wherein y represents a discriminant function output signal;
- wherein w.sub.i represents a coefficient;
- and wherein g.sub.ji represents an exponent;
- accumulating the meta-class signal over a sequence of data frames to generate a meta-class confidence value;
- accumulating the meta-class character classifier output signals over the sequence of data frames to generate a plurality of meta-class character confidence values;
- and
- identifying the text as a function of the meta-class and meta-class character confidence values.
10 more elements
In a computer, a method of identifying text in a handwriting input, the method comprising the following steps:
- receiving a sequence of coordinate-pairs that represent the handwriting input;
- low-pass filtering the sequence of coordinate-pairs;
- removing duplicate coordinate-pairs from the sequence of coordinate-pairs;
- partitioning the sequence of coordinate-pairs into a sequence of data frames;
- extracting a plurality of features from the sequence of data frames;
- distributing the plurality of features to a meta-class classifier for identifying a meta-class comprising a plurality of meta-class characters that are not easily discernible from one another,
- generating a meta-class classifier output signal according to a meta-class polynomial discriminant function;
- distributing the plurality of features to a plurality of meta-class character classifiers for distinguishing between the meta-class characters;
- generating a plurality of meta-class character classifier output signals based on a plurality of meta-character polynomial discriminant functions, each of the meta-class character polynomial discriminant functions having a form ##EQU7## wherein x.sub.j represents the plurality of features;
- wherein i, j, m and n are integers;
- wherein y.sub.l represents one of the meta-class character classifier output signals;
- wherein w.sub.li represents a meta-class coefficient;
- and wherein g.sub.lji represents a meta-class exponent;
- accumulating the meta-class classifier output signal over the sequence of data frames to generate a meta-class confidence value;
- accumulating the meta-class character classifier output signals over the sequence of data frames to generate a plurality of meta-class character confidence values;
- and
- identifying the text as a function of the meta-class and meta-class character confidence values.
14 more elements
An article of manufacture, which comprises:
- a computer-readable memory for directing a computer to recognize a handwriting input, the computer-readable memory having a structure defined by storing a computer program in the computer-readable memory;
- wherein the computer program includes a method for identifying text in the handwriting input, the method comprising the steps of extracting a plurality of features from the handwriting input, generating a meta-class signal by distributing the plurality of features to a meta-class classifier for identifying a meta-class comprising a plurality of meta-class characters that are not easily discernible from one another, distributing the plurality of features to a plurality of character classifiers for distinguishing between the meta-class characters, generating a plurality of character classifier output signals based on a plurality of polynomial discriminant functions, each of the polynomial discriminant functions having a form ##EQU11## wherein x.sub.j represents the plurality of features, wherein i, j, m and n are integers, wherein y represents one of the character classifier output signals, wherein w.sub.i represents a coefficient, and wherein g.sub.ji represents an exponent, and identifying the handwritten text as a function of the meta-class signal and the plurality of character classifier output signals.
A handwriting recognition system for identifying text in a handwriting input, which comprises:
- a feature extractor for extracting a plurality of features from the handwriting input;
- a meta-class classifier generating a meta-class signal in response to the plurality of features, the meta-class classifier identifying a meta-class comprising a plurality of meta-class characters that are not easily discernible from one another:
- a plurality of character classifiers for distinguishing between the meta-class characters, the character classifiers generating a plurality of character classifier output signals based on a plurality of polynomial discriminant functions, each of the polynomial discriminant functions having a form ##EQU13## wherein x.sub.j represents the plurality of features, i, j, m and n are integers, y represents one of the character classifier output signals, w.sub.i represents a coefficient, and g.sub.ji represents an exponent;
- and
- a selector identifying the handwritten text as a function of the meta-class signal and the plurality of character classifier output signals.
2 more elements
A handwriting recognition system for identifying text in a handwriting input, which comprises:
- a pre-processor, responsive to a sequence of coordinate-pairs representing the handwriting input, for low-pass filtering the sequence of coordinate-pairs to generate a filtered sequence;
- a frame extractor for partitioning the filtered sequence into a sequence of data frames;
- a feature extractor for extracting a plurality of features from the sequence of data frames;
- a meta-class classifier generating a meta-class signal in response to the plurality of features, the meta-class classifier identifying a meta-class comprising a plurality of meta-class characters that are not easily discernible from one another:
- a plurality of character classifiers for distinguishing between the meta-class characters, the character classifiers generating a plurality of character classifier output signals based on a plurality of polynomial discriminant functions, each of the polynomial discriminant functions having a form ##EQU15## wherein x.sub.j represents the plurality of features, i, j, m and n are integers, y represents one of the character classifier output signals, w.sub.i represents a coefficient, and g.sub.ji represents an exponent:
- a meta-class accumulator for accumulating the meta-class signal over the sequence of data frames to generate a meta-class confidence value;
- a plurality of meta-character accumulators for accumulating the meta-class character signals over the sequence of data frames to generate a plurality of meta-class character confidence values;
- and
- a selector identifying the text as a function of the meta-class and meta-class character confidence values.
6 more elements
Dependencies are inferred from the claim text.