Michael Jerry Perrone

US Patent:

6567548, May 20, 2003

Filed:

Jan 29, 1999

Appl. No.:

09/240362

Inventors:

Krishna S. Nathan - New York NY
Michael P. Perrone - Yorktown NY
John F. Pitrelli - Danbury CT

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06K 918

US Classification:

382186, 382159, 382179, 382187

Abstract:

A handwriting recognition system and method whereby various character sequences (which are typically âslurredâ together when handwritten) are each modelled as a single character (âcompound character modelâ) so as to provide increased decoding accuracy for slurred handwritten character sequences. In one aspect of the present invention, a method for generating a handwriting recognition system having compound character models comprises the steps of: providing an initial handwriting recognition system having individual character models; collecting and labelling a set of handwriting data; aligning the labelled set of handwriting data; generating compound character data using the aligned handwriting data; and retraining the initial recognition system with the compound character data to generate a new recognition system having compound character models. Once these compound character models are trained, they may be used to accurately decode slurred handwritten character sequences for which compound character models were previously generated. Once recognized, the compound characters are expanded into the constituent individual characters comprising the compound character.

US Patent:

7343041, Mar 11, 2008

Filed:

Feb 19, 2002

Appl. No.:

10/079763

Inventors:

Thomas Yu-Kiu Kwok - Washington Township NJ, US
Michael Peter Perrone - Yorktown Heights NY, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06K 9/00
G06K 9/62

US Classification:

382187, 382224

Abstract:

A handwritten word is transcribed into a list of possibly correct transcriptions of the handwritten word. The list contains a number of text words, and this list is compared with previously stored set of lists of text words. Based on a metric, one or more nearest neighbor lists are selected from the set. A decision is made, according to a number of combination rules, as to which text word in the nearest neighbor lists or the recently transcribed list is the best transcription of the handwritten word. This best transcription is selected as the appropriate text word transcription of the handwritten word. The selected word is compared to a true transcription of the selected word. Machine learning techniques are used when the selected and true transcriptions differ. The machine learning techniques create or update rules that are used to determine which text word of the nearest neighbor lists or the recently transcribed list is the correct transcription of the handwritten word.

US Patent:

7627596, Dec 1, 2009

Filed:

Feb 19, 2002

Appl. No.:

10/079741

Inventors:

Thomas Yu-Kiu Kwok - Washington Township NJ, US
James Randal Moulic - Poughkeepsie NY, US
Kenneth Blair Ocheltree - Ossining NY, US
Michael Peter Perrone - Yorktown Heights NY, US
John Ferdinand Pitrelli - Danbury CT, US
Eugene Henry Ratzlaff - Hopewell Junction NY, US
Gregory Fraser Russell - Yorktown Heights NY, US
Jayashree Subrahmonia - White Plains NY, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06F 17/00

US Classification:

707102, 715268

Abstract:

The techniques in the present invention allow both text and handwritten queries, and the queries can be single-word or multiword. Generally, each handwritten word in a handwritten document is converted to a document stack of words, where each document stack contains a list of text words and a word score of some type for each text word in the list. The query is also converted to one or more stacks of words. A measure is determined from each query and document stack. Documents that meet search criteria in the query are then selected based on the query and the values of the measures. The present invention also performs multiple recognitions, with multiple recognizers, on a handwritten document to create multiple recognized transcriptions of the document. The multiple transcriptions are used for document retrieval. In another embodiment, a single transcription is created from the multiple transcriptions, and the single transcription is used for document retrieval.

US Patent:

7697760, Apr 13, 2010

Filed:

Jan 11, 2008

Appl. No.:

11/972913

Inventors:

Thomas Yu-Kiu Kwok - Washington Township NJ, US
Michael Peter Perrone - Yorktown Heights NY, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06K 9/00
G06K 9/18
G06K 9/72

US Classification:

382186, 382187, 382229

Abstract:

A handwritten word is transcribed into a list of possibly correct transcriptions of the handwritten word. The list contains a number of text words, and this list is compared with previously stored set of lists of text words. Based on a metric, one or more nearest neighbor lists are selected from the set. A decision is made, according to a number of combination rules, as to which text word in the nearest neighbor lists or the recently transcribed list is the best transcription of the handwritten word. This best transcription is selected as the appropriate text word transcription of the handwritten word. The selected word is compared to a true transcription of the selected word Machine learning techniques are used when the selected and true transcriptions differ. The machine learning techniques create or update rules that are used to determine which text word of the nearest neighbor lists or the recently transcribed list is the correct transcription of the handwritten word.

US Patent:

20130346044, Dec 26, 2013

Filed:

Jun 25, 2012

Appl. No.:

13/531887

Inventors:

Ligang LU - New York NY, US
Michael Peter Perrone - Yorktown Heights NY, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06G 7/48
G06F 17/30

US Classification:

703 6, 707802, 707E17001

Abstract:

Systems and techniques for directing data collection. Upon an initial data collection, the uncertainty of all or of a portion or portions of the collected data is evaluated. The collected data may be associated with a region, with portions of the collected data associated with subregions. Further data collection, including changes to or refinement of collection techniques, is undertaken based on evaluations of the uncertainty. Further data collection may be undertaken only for portions of the data for which uncertainty exceeds a threshold. Uncertainty evaluation may be performed at least in part using a model. The model may be an initial hypothesis model, and the model may be optimized as further data is collected, and the optimized model may be used to guide further data collection techniques, with iterations of data collection and model optimization being carried out concurrently.

US Patent:

20130346998, Dec 26, 2013

Filed:

Jun 25, 2012

Appl. No.:

13/531799

Inventors:

Ligang Lu - New York NY, US
Michael Peter Perrone - Yorktown Heights NY, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06F 9/46

US Classification:

718105

Abstract:

Systems and techniques for computational load balancing. A problem space is partitioned into subspaces and the subspaces are assigned to processing nodes. The load of nodes associated with outer subspaces is compared with the load of nodes associated with inner subspaces, and partition boundary adjustments are made based on the relative loads of outer versus inner subspaces.

US Patent:

63269570, Dec 4, 2001

Filed:

Jan 29, 1999

Appl. No.:

9/240213

Inventors:

Krishna S. Nathan - New York NY
Michael P. Perrone - Yorktown NY
John F. Pitrelli - Danbury CT
Eugene H. Ratzlaff - Hopewell Junction NY
Jayashree Subrahmonia - White Plains NY

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G09G 500

US Classification:

345179

Abstract:

System and methods for visually displaying page information in a handwriting recording device such as a personal digital notepad (PDN) device, in which constraints exist which limit the size of a user interface display (e. g. LCD). Various methods allow a user to view detailed page information by selecting one or more available display modes which display the selected information using one or more dynamic icons. In addition, the user can view (via the display) selected portions of handwriting content of a given electronic page, thereby affording the user the opportunity to synchronize the stored handwriting data with the handwritten text.

US Patent:

62564102, Jul 3, 2001

Filed:

Jul 30, 1998

Appl. No.:

9/126251

Inventors:

Krishna S. Nathan - New York NY
Michael P. Perrone - Yorktown NY
Jayashree Subrahmonia - White Plains NY

Assignee:

International Business Machines Corp. - Armonk NY

International Classification:

G06K 900
G06K 918
G06K 962

US Classification:

382187

Abstract:

A method of training a writer dependent handwriting recognition system with handwriting samples of a specific writer comprises the steps of: capturing the handwriting samples of the specific writer; segmenting the handwriting samples of the specific writer; initializing handwriting models associated with the specific writer from the segmented handwriting samples; and refining the initialized handwriting models associated with the specific writer to generate writer dependent handwriting models for use by the writer dependent handwriting recognition system. Preferably, the method also comprises the step of repeating the refining step until the writer dependent handwriting models yield recognition results substantially satisfying a predetermined accuracy threshold.