IP Library › Granted Patent US 11,216,688
Granted Patent B1
US 11,216,688 · App. 16/925,086 · Granted Jan 4, 2022

Handwriting recognition systems and methods

Inventor: Thomas O Binford (Cupertino, CA)
Assignee: Read-Ink Corporation
G06K9/6202G06K9/00416G06K9/00422G06K9/344G06K9/4604G06K9/469G06K9/723G06T7/60G06K2209/01G06T2207/30176
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Quick Facts
Patent No.
US 11,216,688
App. No.
16/925,086
Granted
Jan 4, 2022
Kind
B1
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.

Claims (33)

1. 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 sub-characters of the text comprises:

determining sub-characters based on ovals, loops, retraces, lobes, and sticks;

separating stroke segments from sequences of blended strokes;

estimating these separate stroke segments pairwise at natural transitions based on the sub-character components; and

representing the geometric data of sub-characters as free knot splines parameterized by arc length, with spiral bases with C2 or C1 continuity at knots, and with C0 continuity at discontinuities.

2. 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 sub-characters of the text comprises:

determining sub-characters based on ovals, loops, retraces, lobes, and sticks;

separating stroke segments from sequences of blended strokes;

estimating these separate stroke segments pairwise at natural transitions based on the sub-character components; and

representing the geometric data of sub-characters as free knot splines parameterized by arc length, with spiral bases with C2 or C1 continuity at knots, and with C0 continuity at discontinuities.

3. 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 sub-characters of the text comprises:

determining sub-characters based on ovals, loops, retraces, lobes, and sticks;

separating stroke segments from sequences of blended strokes;

estimating these separate stroke segments pairwise at natural transitions based on the sub-character components; and

representing the geometric data of sub-characters as free knot splines parameterized by arc length, with spiral bases with C2 or C1 continuity at knots, and with C0 continuity at discontinuities.

Continuity (1)
Division 16419635 · May 22, 2019
Cited By (1)
US 12,249,112