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US 11,232,322 B1Granted
Handwriting recognition systems and methods
AssigneeRead-Ink Corporation
InventorThomas O Binford
Life of this patent
Estimating the term…
Abstract
The present disclosure includes systems and methods for handwriting recognition. Handwriting data is received. Geometric data of text in handwriting data is determined. Sub-characters of the text are determined. Sub-characters of text are matched to a model. Most probable characters of the text is determined based on the matching.
Claims14
A method for recognizing handwriting, the method comprising:
- receiving handwriting data;
- determining geometric data of text in handwriting data;
- determining sub-characters of the text;
- matching sub-characters of text to a model;
- and
- determining most probable characters of the text based on said matching,
- wherein matching sub-characters of text to a model comprises:
- mapping the model to character instances by curves, pairs of curves, and pairs of pairs of curves,
- mapping structured models of characters composed of sub-characters;
- and
- representing the mapped sub-characters and characters as a directed acyclic graph (DAG).
8 more elements
A method for recognizing handwriting, the method comprising:
- receiving handwriting data;
- determining geometric data of text in handwriting data;
- determining sub-characters of the text;
- matching sub-characters of text to a model;
- and
- determining most probable characters of the text based on said matching,
- wherein determining most probable characters of the text based on the said matching comprises estimating k-best character probabilities from k-best graph search (A*) of a directed acyclic graph of alternative sub-character and character log probabilities of multiple character hypotheses.
4 more elements
A method for recognizing handwriting, the method comprising:
- receiving handwriting data;
- determining geometric data of text in handwriting data;
- determining sub-characters of the text;
- matching sub-characters of text to a model;
- determining most probable characters of the text based on said matching;
- initializing parameters of handwriting geometry based on approximately two characters of text in the received handwriting data;
- and
- adapting to the strata of the current document sub-character geometry over the course of analysis of the document;
- wherein individual writers have few strata and there are few strata across all writers.
6 more elements
A method for recognizing handwriting, the method comprising:
- receiving handwriting data;
- determining geometric data of text in handwriting data;
- determining sub-characters of the text;
- matching sub-characters of text to a model;
- determining most probable characters of the text based on said matching;
- and
- estimating the probability of a pair or tuple of received characters based on sub-word linguistic evidence of graphemes, syllables and subsyllables, and affixes.
4 more elements
A non-transitory computer-readable storage medium storing instructions for handwriting recognition, the instructions when executed by one or more processors causing the one or more processors to perform steps comprising:
- receiving handwriting data;
- determining geometric data of text in handwriting data;
- determining sub-characters of the text;
- matching sub-characters of text to a model;
- and
- determining most probable characters of the text based on said matching,
- wherein matching sub-characters of text to a model comprises:
- mapping the model to character instances by curves, pairs of curves, and pairs of pairs of curves,
- mapping structured models of characters composed of sub-characters;
- and
- representing the mapped sub-characters and characters as a directed acyclic graph (DAG).
8 more elements
A non-transitory computer-readable storage medium storing instructions for handwriting recognition, the instructions when executed by one or more processors causing the one or more processors to perform steps comprising:
- receiving handwriting data;
- determining geometric data of text in handwriting data;
- determining sub-characters of the text;
- matching sub-characters of text to a model;
- and
- determining most probable characters of the text based on said matching,
- wherein the matching sub-characters of text to a model comprises:
- estimating empirical conditional probability P(dlh) of parameter data based on hypothesis from order statistics of a parameter;
- using signed functional distance that is not scalar;
- and
- estimating non-parameterized empirical probability over stratified character and sub-character populations.
8 more elements
A non-transitory computer-readable storage medium storing instructions for handwriting recognition, the instructions when executed by one or more processors causing the one or more processors to perform steps comprising:
- receiving handwriting data;
- determining geometric data of text in handwriting data;
- determining sub-characters of the text;
- matching sub-characters of text to a model;
- and
- determining most probable characters of the text based on said matching,
- wherein determining most probable characters of the text based on the said matching comprises estimating k-best character probabilities from k-best graph search (A*) of a directed acyclic graph of alternative sub-character and character log probabilities of multiple character hypotheses.
4 more elements
A non-transitory computer-readable storage medium storing instructions for handwriting recognition, the instructions when executed by one or more processors causing the one or more processors to perform steps comprising:
- receiving handwriting data;
- determining geometric data of text in handwriting data;
- determining sub-characters of the text;
- matching sub-characters of text to a model;
- determining most probable characters of the text based on said matching;
- initializing parameters of handwriting geometry based on approximately two characters of text in the received handwriting data;
- and
- adapting to the strata of the current document sub-character geometry over the course of analysis of the document;
- wherein individual writers have few strata and there are few strata across all writers.
6 more elements
A non-transitory computer-readable storage medium storing instructions for handwriting recognition, the instructions when executed by one or more processors causing the one or more processors to perform steps comprising:
- receiving handwriting data;
- determining geometric data of text in handwriting data;
- determining sub-characters of the text;
- matching sub-characters of text to a model;
- determining most probable characters of the text based on said matching;
- and
- estimating the probability of a pair or tuple of received characters based on sub-word linguistic evidence of graphemes, syllables and subsyllables, and affixes.
4 more elements
A computer system for handwriting recognition, the computer system comprising:
- one or more computer processors;
- and one or more non-transitory computer-readable storage media, the storage media storing computer program instructions executable by the one or more computer processors to perform steps comprising:
- receiving handwriting data;
- determining geometric data of text in handwriting data;
- determining sub-characters of the text;
- matching sub-characters of text to a model;
- and
- determining most probable characters of the text based on said matching,
- wherein matching sub-characters of text to a model comprises:
- mapping the model to character instances by curves, pairs of curves, and pairs of pairs of curves,
- mapping structured models of characters composed of sub-characters;
- and
- representing the mapped sub-characters and characters as a directed acyclic graph (DAG).
10 more elements
A computer system for handwriting recognition, the computer system comprising:
- one or more computer processors;
- and one or more non-transitory computer-readable storage media, the storage media storing computer program instructions executable by the one or more computer processors to perform steps comprising:
- receiving handwriting data;
- determining geometric data of text in handwriting data;
- determining sub-characters of the text;
- matching sub-characters of text to a model;
- and
- determining most probable characters of the text based on said matching,
- wherein the matching sub-characters of text to a model comprises:
- estimating empirical conditional probability P(dlh) of parameter data based on hypothesis from order statistics of a parameter;
- using signed functional distance that is not scalar;
- and
- estimating non-parameterized empirical probability over stratified character and sub-character populations.
10 more elements
A computer system for handwriting recognition, the computer system comprising:
- one or more computer processors;
- and one or more non-transitory computer-readable storage media, the storage media storing computer program instructions executable by the one or more computer processors to perform steps comprising:
- receiving handwriting data;
- determining geometric data of text in handwriting data;
- determining sub-characters of the text;
- matching sub-characters of text to a model;
- and
- determining most probable characters of the text based on said matching,
- wherein determining most probable characters of the text based on the said matching comprises estimating k-best character probabilities from k-best graph search (A*) of a directed acyclic graph of alternative sub-character and character log probabilities of multiple character hypotheses.
6 more elements
A computer system for handwriting recognition, the computer system comprising:
- one or more computer processors;
- and one or more non-transitory computer-readable storage media, the storage media storing computer program instructions executable by the one or more computer processors to perform steps comprising:
- receiving handwriting data;
- determining geometric data of text in handwriting data;
- determining sub-characters of the text;
- matching sub-characters of text to a model;
- determining most probable characters of the text based on said matching;
- initializing parameters of handwriting geometry based on approximately two characters of text in the received handwriting data;
- and
- adapting to the strata of the current document sub-character geometry over the course of analysis of the document;
- wherein individual writers have few strata and there are few strata across all writers.
8 more elements
A computer system for handwriting recognition, the computer system comprising:
- one or more computer processors;
- and one or more non-transitory computer-readable storage media, the storage media storing computer program instructions executable by the one or more computer processors to perform steps comprising:
- receiving handwriting data;
- determining geometric data of text in handwriting data;
- determining sub-characters of the text;
- matching sub-characters of text to a model;
- determining most probable characters of the text based on said matching;
- and
- estimating the probability of a pair or tuple of received characters based on sub-word linguistic evidence of graphemes, syllables and subsyllables, and affixes.
6 more elements
Dependencies are inferred from the claim text.