Online Script Independent Recognition of Handwritten Sub-Word Units and Words

• US 20120114245A1
• Filed: 11/09/2011
• Published: 05/10/2012
• Est. Priority Date: 11/09/2010
• Status: Active Grant

• Current Assignee: TATA Consultancy Services Limited (Tata Sons Pvt Ltd.)
• Original Assignee: TATA Consultancy Services Limited (Tata Sons Pvt Ltd.)
• Inventors: Lakshmanan, Lajish Vimala, Kopparapu, Sunil Kumar
• Granted Patent: US 8,768,062 B2
• Time in Patent Office: Days
• US Class Current: 382/186
• CPC Class Codes: G06F 3/04883 for inputting data by handwriting, e.g. gesture or text
• CPC Class Codes: G06V 10/98 Detection or correction of errors, e.g. by rescanning the pattern or by human intervention; Evaluation of the quality of the acquired patterns
• CPC Class Codes: G06V 30/1423 the instrument generating sequences of position coordinates corresponding to handwriting preprocessing or recognising digital ink G06V30/32
• CPC Class Codes: G06V 30/333 Preprocessing; Feature extraction

Abstract

The present invention relates to a method and system for online script independent recognition of handwritten sub-word unit and words. More particularly the present invention relates to a system and method which enables online recognition of script independent sub-word unit and words by recognizing the written individual strokes prior to recognition of sub-word unit and words. The present invention provides an easy and natural to use method for handwritten sub-word unit and word recognition, wherein the application can be deployed on the existing communication means.

Claims

1. A method for online handwritten sub-word unit recognition on a communication means, using an application stored in a memory of a communication means;

wherein the said method comprises the processor implemented steps of;

a. providing an online handwritten text input using an input means through an user interface to the said communication means;

b. sending the said online handwritten text input to spatio-temporal analysis module of the application;

wherein the said spatio-temporal analysis module further comprises of a recognition engine for recognizing primitive strokes prior to sub-word units;

c. subjecting the text input of step b) to stroke extraction and separation module of the application to extract and separate the strokes by comparing the said strokes to a primitive stroke database;

d. subjecting the data of strokes obtained from step c) to the pre-processing module to pre-process the said extracted, separated and identified individual strokes by;

i. reducing or removing the noise created due to the slow movement of the said input means using a noise removal module of the said pre-processing module to obtain noise free smooth data, and

ii. optionally normalizing the size of the online handwritten text data by using the size normalization module of the pre-processing module;

e. subjecting the pre-processed primitive stroke data of step d) to feature extraction module for modeling and representing the online handwritten text input;

wherein the feature extraction module further comprises of;

i. critical point identification module pertaining algorithms for identifying the critical points in the pre-processed smoothed data, and

ii. fuzzy directional features for representing the strokes in the pre-processed smoothed data;

f. subjecting the feature extracted data of step e) to stroke level recognition module for recognizing the primitive strokes, and further concatenating the said primitive strokes to form a sequence of strokes to further form a sub-word unit;

wherein the stroke level recognition module further analyzes for any errors in the recognition of strokes using an evaluation and error analysis module;

g. in case of any error, the evaluation and error analysis module helps in improving the stroke recognition;

h. subjecting the sequence of recognized strokes of step f) for sub-word unit formation and sub-word unit recognition using the sub-word unit level recognition module;

wherein the sub-word units are formed on the basis of the sub-word unit boundary information obtained from the sub-word unit boundary segmentation module and the defined rules for sub-word unit formation of the said sub-word unit level recognition module;

wherein the sub-word unit recognition module further analyzes for any error in the recognition;

i. In case of any error, the sub-word unit recognition results are backtracked through the error analysis module and modified based on the failure of the sub-word unit formation namely to put together a sequence strokes to form a sub-word unit.

2. A method as claimed in claim 1, wherein the said communication means comprises of mobile phone, a Personal Digital Assistant, PDA, palm-top, mobile digital assistant, computer, laptop, notebook, personal computer or any portable communication device.

3. A method as claimed in claim 1, wherein the input means of the said communication means comprises of a special electronic pen, stylus or stick.

4. A method as claimed in claim 1, wherein the user interface comprises of writing panel, an electronic tablet or the pressure sensitive touch screen of the communication means.

5. A method as claimed in claim 1, wherein the user interface is receptive to online handwritten text input for capturing and storing time ordered (x, y) sequence of handwritten text with stroke begin or pen down and stroke end or pen up information.

6. A method as claimed in claim 1, wherein the sub-word units recognized and formed are further subjected to word level recognition module to recognize and form words, using the lexicon based word level knowledge or language model dictionary along with the obtained spatio-temporal information obtained.

7. A system for online handwritten sub-word unit recognition;

wherein the said system comprising;

a. at least one communication means having an application stored in a memory of the said communication means;

wherein the said communication means further comprises of an input means to provide online handwritten text input via the user interface of the said communication means; and

b. the said application for online handwritten sub-word unit recognition comprising;

script independent modules; and

script dependent module.

8. A system as claimed in claim 7, wherein the said script independent modules comprises of stroke extraction and separation module, pre-processing module, feature extraction module, stroke level recognition module, evaluation and error analysis module and sub-word unit level recognition module.

9. A system as claimed in claim 8, wherein the said stroke extraction and separation module extracts and separates the strokes from the online handwritten text input by comparing the said strokes to a primitive stroke database

10. A system as claimed in claim 8, wherein the said pre-processing module further consists of noise removal module and a size normalization module to provide pre-processed smoothed data.

11. A system as claimed in claim 10, wherein the said noise removal module is used for reducing or removing the noise created due to slow movement of the input means of the said communication means.

12. A system as claimed in claim 10, wherein the said size normalization module is used for normalizing the size of the online handwritten text input.

13. A system as claimed in claim 8, wherein the said feature extraction module further consists of critical points identification module and fuzzy directional feature extraction module.

14. A system as claimed in claim 13, wherein the said critical points identification module consists of algorithms for identifying the critical points in the pre-processed smoothed data.

15. A system as claimed in claim 13, wherein the said fuzzy directional feature extraction module models and represents the strokes in the pre-processed smoothed data.

16. A system as claimed in claim 8, wherein the said stroke level recognition module recognizes the primitive strokes and further concatenates the said primitive strokes to form a sequence of strokes to further form a sub-word unit.

17. A system as claimed in claim 8, wherein the said sub-word unit level recognition module further consists of sub-word unit boundary segmentation module and rules based sub-word unit creation module to form sub-word units based on the sub-word unit boundary information and rules for sub-word unit formation.

18. A system as claimed in claim 17, wherein the said rules based sub-word unit creation module is script dependent.

19. A system as claimed in claim 8, wherein the said evaluation and error analysis module evaluates and analyses the error to improve stroke recognition and sub-word unit recognition.

20. A system as claimed in claim 7, wherein the sub-word units recognized and formed are further concatenated to form words using word level recognition module supported by lexicon based word level knowledge or language model dictionary.

21. A system as claimed in claim 20, wherein the said word level recognition module and lexicon based word level knowledge or language model dictionary are script dependent modules

22. A system as claimed in claim 7, wherein the said script dependent modules further consists of script independent spatio-temporal analysis module;

wherein the said spatio-temporal analysis module consists of a recognition engine for recognizing primitive strokes prior to sub-word unit based on the spatial information of each stroke.

23. A system as claimed in claim 7, wherein the said communication means comprises of mobile phone, a Personal Digital Assistant, PDA, palm-top, mobile digital assistant, computer, laptop, notebook, personal computer or any other portable communication device.

24. A system as claimed in claim 7, wherein the input means of the said communication means comprises of a pen, special electronic pen, stylus or stick.

25. A system as claimed in claim 7, wherein the user interface comprises of a special writing panel or an electronic tablet or the pressure sensitive touch screen of the communication means.

26. A system as claimed in claim 7, wherein the user interface is receptive to online handwritten text input for capturing and storing time ordered (x, y) sequence of handwritten text with stroke begin and end or pen up and pen down information.