US20060088215A1 - Handwriting recognition system - Google Patents
Handwriting recognition system Download PDFInfo
- Publication number
- US20060088215A1 US20060088215A1 US11/250,378 US25037805A US2006088215A1 US 20060088215 A1 US20060088215 A1 US 20060088215A1 US 25037805 A US25037805 A US 25037805A US 2006088215 A1 US2006088215 A1 US 2006088215A1
- Authority
- US
- United States
- Prior art keywords
- stylus
- recognition system
- handwriting recognition
- classifier
- signal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
- G06V30/10—Character recognition
- G06V30/14—Image acquisition
- G06V30/142—Image acquisition using hand-held instruments; Constructional details of the instruments
- G06V30/1423—Image acquisition using hand-held instruments; Constructional details of the instruments the instrument generating sequences of position coordinates corresponding to handwriting
Definitions
- the present invention relates to a handwriting recognition system and more particularly to a hardware and an algorithm for implementing such a system.
- PCT application number GB98/0316 Publication No. WO99/223378
- a portable computer in the form of a pen-type casing.
- Incorporated within the casing is at least one accelerometer which is used to detect movement of the pen with respect to its environment.
- the instrument for handwriting it is possible to effect data entry or transmission of signals reflecting movement, the user using either a pen tip mounted switch or a finger operated switch to indicate that movement is effecting a written input.
- a handwriting recognition system comprising means responsive to input analogue signals representative of movement of a handheld writing device, sampling means to provide signals representative of the acceleration of the writing device in at least x axis and y axis channels at a predetermined capture sampling rate, and filtering means to remove dc level components and to provide smoothing of the output whereby signals representative of movement of the pen over a period are supplied to a classifier for comparison with a template representative of characters formed.
- the classifier may use hidden Markov modelling (HMM) techniques using a large number of states to determine the character defined by movement.
- HMM hidden Markov modelling
- the system may include an input indicative of a user's intention that the movement is representative of character writing.
- a method of analysing signals from a moving handheld device comprising sampling signals at a predetermined rate, passing signals through a bandpass filter to remove dc level and excess acceleration components, sampling the filtered output to provide a series of vectors representing the position of the handheld device at periodic intervals and using a classifier to compare the sample sets with predetermined templates to determine the character for output.
- FIG. 1 is a block schematic diagram of the system
- FIG. 2 shows relative positioning of the x and y axis of the handwriting device of FIG. 1 ;
- FIG. 3 is a schematic diagram of the handheld writing device of FIG. 1 in a particular position
- FIG. 4 shows relative input and output vector streams from the system of FIG. 1 ;
- FIGS. 5 to 9 show comparative templates for a number of different letters.
- an input device 1 such as a stylus produces x and y vector streams 2 and 3 which are fed into a sampling unit 4 .
- the outputs x and y are generally from accelerometers or other position sensing devices within the stylus 1 .
- Also feeding the sampling unit 4 is an output 5 from a switch indicated here as being in the nib section of the stylus 1 such that contact between the switch 6 and a surface is indicative of the stylus being used in a writing mode.
- a switch indicated here as being in the nib section of the stylus 1 such that contact between the switch 6 and a surface is indicative of the stylus being used in a writing mode.
- the nib switch 6 when incorporated in a non-surface contacting stylus, such as that disclosed in the previously referred PCT application, may be replaced by a user operable switch.
- the output of the sampling unit 4 which samples the incoming streams at 60 Hz for example, is passed to a bandpass filter arrangement 7 and thence to a down sampling unit 8 which produces digitised vectors x and y over a period of time.
- the x and y vectors are passed to a classifier 9 , which uses a hidden Markov model to carry out a comparison between the vectors and templates representing written characters.
- the classifier 9 may be arranged to output to a visual display 10 .
- the stylus 1 for example comprises a simple plastic casing containing the electronics for transferring information to a PC.
- Two accelerometers mounted in the stylus, for example, are used to produced the x and y outputs.
- the nib switch is a simple on/off switch connected to determine when pressure is being applied to the pen nib and can therefore detect when a pen for stylus 1 is writing.
- the two accelerometers mounted in the top of the pen measure acceleration across their plane such that effectively they measure acceleration along the x axis 11 and the y axis 12 of the writing surface 14 .
- the acceleration measured by the sensors is made up of two components, acceleration due to gravity and the acceleration as a result of stylus movement. It will be appreciated that the acceleration due to gravity is always present, such that when the pen is exactly horizontal both sensors would measure acceleration of 1 g.
- the accelerometers are subject to Sin ⁇ 1 g where ⁇ is the inclination angle of the stylus 1 .
- acceleration as a result of the pen moving is produced by the acceleration and deceleration effect as the user writes.
- y total y g +y movement
- x total x g +x movement
- the remaining items of FIG. 1 are incorporated in a computer unit, for example a PC, and three signals, as previously indicated, 2 , 3 and 5 being the two acceleration signals and binary signal from the pen switch are provided to the PC.
- the two acceleration signals are read into a normal PC using an RS232 port and the binary switch signal by means of the games port of a sound card.
- the sampling section must sample sufficiently regularly to capture the movement of the pen but preferably should not over-sample, which would result in a waste of processing and storage within the PC. It has been found satisfactory for the purposes of the current embodiment to sample at a rate of 60 Hz.
- the acceleration signals for each channel are read in as two byte words giving a dynamic range for each acceleration signal from 0 to 65535.
- the pen nib switch is similarly sampled at the same rate.
- the accelerometer signals are partly dependent on a component of the earth's gravitation field passing through the accelerometer of the stylus 1 . This results in an almost constant dc level present on the output corresponding to the average pen angle ⁇ while writing.
- the bandpass filter 7 is thus arranged to filter the signals from the two accelerometers to remove the offsets. Additionally, the bandpass filter smoothes the output from the sensors thus correcting for instability introduced by the user so that the smoothed output from the sensors increases robustness and facilitates matching between the x and y vectors and stored templates.
- the pen nib switch (or manually operable switch) indicates whether the stylus 1 was being used in a writing mode or not.
- the down sampling process 8 uses the information to down sample acceleration samples and to retain only those when it was known that the stylus 1 was writing.
- the x axis and y axis vectors are as shown at 15 and 16 .
- the down sampling vectors need only be taken into account when the nib switch signal indicator 17 is high. This will reduce the number of samples significantly so that the output from the down sampling process is a time series of two dimensional vectors x and y as indicated at 18 and 19 .
- the vector stream is passed to the classifier stage 9 which takes in a series of vectors representing the acceleration measurements made within a given word. These are then compared to a set of templates which cover the range of words within the system vocabulary and the word which matches most closely with the unknown input word is deemed the recognised word.
- the classifier is a hidden Markov model. Such models have been widely used in speech recognition and using a large number of states in the hidden Markov model will give the best performance for corresponding handwriting recognition.
- the display 10 which displays the output from the PC allows display of a word, for example, on a screen.
- a typical single accelerometer output can be seen respectively for the letters c, b, f and h in FIGS. 5 to 8 .
- the template developed here shows three entries on a single accelerometer for each of the letters.
- f, b, h and c are shown in comparison so that a suitable template for comparison may be derived. It will be appreciated that the combination of an x accelerometer trace and a y accelerometer trace will serve further to emphasise the difference between each input letter.
- Bandpass filtering in digital form to remove dc components and high frequency components increases the reliability of the recognition process and therefore the reliability of the interpretation of the stylus input 1 . It will be appreciated that where the stylus 1 carries other components, for example an internal processing arrangement, some of the functions may be transferred from the PC to the stylus 1 . All of the components of sampling, bandpass filtering, down sampling and classifying can be implemented in a suitable computer program.
Landscapes
- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Character Discrimination (AREA)
Abstract
In order to improve the accuracy of recognition of hand-written input using a stylus, output signals from a plurality of accelerometers representing x and y axis acceleration and deceleration are sampled at a predetermined rate and passed through a digital bandpass filter to remove high frequency components and dc components arising from gravity. X and y vectors derived from the original x and y input signals are passed to a classifier using a hidden Markov model. Bandpass filtering improves the robustness of the interpretation of the vectors against stored templates which may be templates of individual characterisations or of whole words.
Description
- This is a division of our copending commonly assigned application Ser. No. 09/914,262 filed Aug. 24, 2001 which was, in turn, a 35 U.S.C. §371 US national phase of PCT/GB00/01052 filed Mar. 21, 2000 and claiming priority from European application 99302270.6 filed Mar. 24, 1999.
- 1. Field of the Invention
- The present invention relates to a handwriting recognition system and more particularly to a hardware and an algorithm for implementing such a system.
- 2. Related Art
- In PCT application number GB98/0316 (Publication No. WO99/22338) there is disclosed a portable computer in the form of a pen-type casing. Incorporated within the casing is at least one accelerometer which is used to detect movement of the pen with respect to its environment. By using the instrument for handwriting it is possible to effect data entry or transmission of signals reflecting movement, the user using either a pen tip mounted switch or a finger operated switch to indicate that movement is effecting a written input.
- There are many other pen-type input devices on the market in addition to stylus scroll pallets typically used in so-called palm top computers where handwriting recognition has been used. Such devices often require very precise movement which may not reflect natural handwriting movements for the user. One of the problems which makes characteristic handwriting recognition difficult is that while the underlying movement made by an individual to represent a particular letter may be consistent an element reflecting user movements due to stress and other factors will be present.
- According to an exemplary embodiment the present invention there is provided a handwriting recognition system comprising means responsive to input analogue signals representative of movement of a handheld writing device, sampling means to provide signals representative of the acceleration of the writing device in at least x axis and y axis channels at a predetermined capture sampling rate, and filtering means to remove dc level components and to provide smoothing of the output whereby signals representative of movement of the pen over a period are supplied to a classifier for comparison with a template representative of characters formed.
- The classifier may use hidden Markov modelling (HMM) techniques using a large number of states to determine the character defined by movement. The system may include an input indicative of a user's intention that the movement is representative of character writing.
- According to a feature of the present there is provided a method of analysing signals from a moving handheld device, the method comprising sampling signals at a predetermined rate, passing signals through a bandpass filter to remove dc level and excess acceleration components, sampling the filtered output to provide a series of vectors representing the position of the handheld device at periodic intervals and using a classifier to compare the sample sets with predetermined templates to determine the character for output.
- A handwriting recognition system in according with the invention will now be described by way of example only with reference to the accompanying drawing of which:
-
FIG. 1 is a block schematic diagram of the system; -
FIG. 2 shows relative positioning of the x and y axis of the handwriting device ofFIG. 1 ; -
FIG. 3 is a schematic diagram of the handheld writing device ofFIG. 1 in a particular position; -
FIG. 4 shows relative input and output vector streams from the system ofFIG. 1 ; and - FIGS. 5 to 9 show comparative templates for a number of different letters.
- Referring first to
FIG. 1 , aninput device 1 such as a stylus produces x andy vector streams sampling unit 4. The outputs x and y are generally from accelerometers or other position sensing devices within thestylus 1. Also feeding thesampling unit 4 is anoutput 5 from a switch indicated here as being in the nib section of thestylus 1 such that contact between theswitch 6 and a surface is indicative of the stylus being used in a writing mode. It will be appreciated that thenib switch 6 when incorporated in a non-surface contacting stylus, such as that disclosed in the previously referred PCT application, may be replaced by a user operable switch. - The output of the
sampling unit 4, which samples the incoming streams at 60 Hz for example, is passed to abandpass filter arrangement 7 and thence to a downsampling unit 8 which produces digitised vectors x and y over a period of time. The x and y vectors are passed to aclassifier 9, which uses a hidden Markov model to carry out a comparison between the vectors and templates representing written characters. Theclassifier 9 may be arranged to output to avisual display 10. - More specifically, the
stylus 1 for example comprises a simple plastic casing containing the electronics for transferring information to a PC. Two accelerometers mounted in the stylus, for example, are used to produced the x and y outputs. The nib switch is a simple on/off switch connected to determine when pressure is being applied to the pen nib and can therefore detect when a pen forstylus 1 is writing. - Turning briefly to
FIG. 2 , the two accelerometers mounted in the top of the pen measure acceleration across their plane such that effectively they measure acceleration along thex axis 11 and they axis 12 of thewriting surface 14. The acceleration measured by the sensors is made up of two components, acceleration due to gravity and the acceleration as a result of stylus movement. It will be appreciated that the acceleration due to gravity is always present, such that when the pen is exactly horizontal both sensors would measure acceleration of 1 g. As the angle of the pen to the horizontal changes (as shown for example inFIG. 3 ), the accelerometers are subject to Sin θ×1 g where θ is the inclination angle of thestylus 1. - The other component, acceleration as a result of the pen moving is produced by the acceleration and deceleration effect as the user writes.
- The acceleration of the two sensors xtotal and ytotal can be expressed as
y total =y g +y movement and x total =x g +x movement
The remaining items ofFIG. 1 are incorporated in a computer unit, for example a PC, and three signals, as previously indicated, 2, 3 and 5 being the two acceleration signals and binary signal from the pen switch are provided to the PC. - In one embodiment the two acceleration signals are read into a normal PC using an RS232 port and the binary switch signal by means of the games port of a sound card.
- The sampling section must sample sufficiently regularly to capture the movement of the pen but preferably should not over-sample, which would result in a waste of processing and storage within the PC. It has been found satisfactory for the purposes of the current embodiment to sample at a rate of 60 Hz. The acceleration signals for each channel are read in as two byte words giving a dynamic range for each acceleration signal from 0 to 65535. The pen nib switch is similarly sampled at the same rate.
- As previously mentioned, the accelerometer signals are partly dependent on a component of the earth's gravitation field passing through the accelerometer of the
stylus 1. This results in an almost constant dc level present on the output corresponding to the average pen angle θ while writing. Thebandpass filter 7 is thus arranged to filter the signals from the two accelerometers to remove the offsets. Additionally, the bandpass filter smoothes the output from the sensors thus correcting for instability introduced by the user so that the smoothed output from the sensors increases robustness and facilitates matching between the x and y vectors and stored templates. - Turning now to
FIG. 4 , for each sample received on the PC from the accelerometers, the pen nib switch (or manually operable switch) indicates whether thestylus 1 was being used in a writing mode or not. The downsampling process 8 uses the information to down sample acceleration samples and to retain only those when it was known that thestylus 1 was writing. Thus, considerFIG. 4 , assuming that the x axis and y axis vectors are as shown at 15 and 16, then the down sampling vectors need only be taken into account when the nibswitch signal indicator 17 is high. This will reduce the number of samples significantly so that the output from the down sampling process is a time series of two dimensional vectors x and y as indicated at 18 and 19. - Having completed processing of the acceleration measurement from the
stylus 1 the vector stream is passed to theclassifier stage 9 which takes in a series of vectors representing the acceleration measurements made within a given word. These are then compared to a set of templates which cover the range of words within the system vocabulary and the word which matches most closely with the unknown input word is deemed the recognised word. In this system the classifier is a hidden Markov model. Such models have been widely used in speech recognition and using a large number of states in the hidden Markov model will give the best performance for corresponding handwriting recognition. - The
display 10, which displays the output from the PC allows display of a word, for example, on a screen. - While the above handwriting recognition system is intended for use with a series of known words which, depending on the system vocabulary entered into the PC, may be a large number, it will be possible to use the same kind of system to validate single character entry. Using single character recognition and using cursive entry it is still possible to build individual words which may not be present in the vocabulary. There may be a lower level of confidence in words created rather than template determined. However, over time, the vocabulary may be expanded where multiple entries of the same word have occurred such that higher confidence levels may be achieved.
- A typical single accelerometer output can be seen respectively for the letters c, b, f and h in FIGS. 5 to 8. In each case the template developed here shows three entries on a single accelerometer for each of the letters.
- In
FIG. 9 , f, b, h and c are shown in comparison so that a suitable template for comparison may be derived. It will be appreciated that the combination of an x accelerometer trace and a y accelerometer trace will serve further to emphasise the difference between each input letter. - Bandpass filtering in digital form to remove dc components and high frequency components increases the reliability of the recognition process and therefore the reliability of the interpretation of the
stylus input 1. It will be appreciated that where thestylus 1 carries other components, for example an internal processing arrangement, some of the functions may be transferred from the PC to thestylus 1. All of the components of sampling, bandpass filtering, down sampling and classifying can be implemented in a suitable computer program.
Claims (16)
1. (canceled)
2. A handwriting recognition system as in claim 5 , in which the classifier uses a hidden Markov model for comparison purposes.
3. A handwriting recognition system as in claim 5 , in which the sampling means, filtering means and classifier are implemented in a digital computer environment.
4. (canceled)
5. A handwriting recognition system comprising:
a stylus including at least one accelerometer to detect acceleration of the stylus with respect to gravitational pull and to provide analog signals representative of movement of the stylus;
a signal sampler responsive to the analog signals to derive a plurality of signal streams therefrom at a predetermined sampling rate, respective ones of said plurality of signal streams respectively representing acceleration of the stylus in at least an x-axis channel and a y-axis channel;
a bandpass filter acting upon the signal streams to remove low frequency and constant components caused by fixed angular gravitational pull on the stylus and to remove high frequency components caused by operator instability to provide a corresponding plurality of signal streams representing only wanted acceleration components; and
a classifier acting on the corresponding plurality of signal streams to produce data defining alpha-numeric characters.
6. A handwriting recognition system as in claim 5 in which the stylus includes a switch which controls the signal sampler so that sampling occurs only when the switch indicates that the operator intends writing.
7. A handwriting recognition system comprising:
a stylus including two accelerometers respectively detecting acceleration of the stylus with respect to gravity in an x-axis and a y-axis direction and providing respective analogue signals representative of acceleration of the stylus in the x-axis and the y-axis direction;
a signal sampler acting upon the respective analog signal streams to derive a respective plurality of signal streams therefrom at a predetermined sampling rate:
a bandpass filter acting upon the plurality of signal streams to remove low frequency and constant components caused by fixed angular gravitational pull on the stylus and to remove high frequency components caused by operator instability to provide a corresponding plurality of signal streams representing only wanted acceleration components; and
a classifier acting on the corresponding plurality of signal streams to produce data defining alpha numeric characters.
8. A handwriting recognition system as in claim 7 in which the classifier uses a hidden Markov model for comparison purposes.
9. A handwriting recognition system as in claim 7 in which the signal sampler, bandpass filter and classifier are implemented in a digital computer.
10. A handwriting recognition system as in claim 7 in which the stylus includes a switch which controls the signal sampler so that sampling occurs only when the switch indicates that the operator intends writing.
11. A handwriting recognition system as in claim 2 , in which the sampling means, filtering means and classifier are implemented in a digital computer environment.
12. A handwriting recognition system as in claim 2 in which the stylus includes a switch which controls the signal sampler so that sampling occurs only when the switch indicates that the operator intends writing.
13. A handwriting recognition system as in claim 8 in which the signal sampler, bandpass filter and classifier care implemented in a digital computer.
14. A handwriting recognition system as in claim 8 which the stylus includes a switch which controls the signal sampler so that sampling occurs only when the switch indicates that the operator intends writing.
15. A method for processing accelerometer signals from a handheld movable electronic writing device, said method comprising:
bandpass filtering said accelerometer signals to reduce (a) dc components caused by gravity and (b) high frequency components caused by operator instability; and
thereafter analyzing the resulting bandpass-filtered signals to determine a recognized electronic writing output.
16. Apparatus for processing accelerometer signals from a handheld movable electronic writing device, said method comprising:
a bandpass filter arranged to process said accelerometer signals by reducing (a) dc components caused by gravity and (b) high frequency components caused by operator instability; and
signal analyzing and recognition structure arranged to analyze the resulting bandpass filtered signals to determine a recognized electronic writing output.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US11/250,378 US20060088215A1 (en) | 1999-03-24 | 2005-10-17 | Handwriting recognition system |
Applications Claiming Priority (5)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP99302270 | 1999-03-24 | ||
EP99302270.6 | 1999-03-24 | ||
PCT/GB2000/001052 WO2000057349A1 (en) | 1999-03-24 | 2000-03-21 | Handwriting recognition system |
US09/914,262 US7054510B1 (en) | 1999-03-24 | 2000-03-21 | Handwriting recognition system |
US11/250,378 US20060088215A1 (en) | 1999-03-24 | 2005-10-17 | Handwriting recognition system |
Related Parent Applications (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/GB2000/001052 Division WO2000057349A1 (en) | 1999-03-24 | 2000-03-21 | Handwriting recognition system |
US09/914,262 Division US7054510B1 (en) | 1999-03-24 | 2000-03-21 | Handwriting recognition system |
Publications (1)
Publication Number | Publication Date |
---|---|
US20060088215A1 true US20060088215A1 (en) | 2006-04-27 |
Family
ID=8241290
Family Applications (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/914,262 Expired - Fee Related US7054510B1 (en) | 1999-03-24 | 2000-03-21 | Handwriting recognition system |
US11/250,378 Abandoned US20060088215A1 (en) | 1999-03-24 | 2005-10-17 | Handwriting recognition system |
Family Applications Before (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/914,262 Expired - Fee Related US7054510B1 (en) | 1999-03-24 | 2000-03-21 | Handwriting recognition system |
Country Status (4)
Country | Link |
---|---|
US (2) | US7054510B1 (en) |
EP (1) | EP1181665A1 (en) |
AU (1) | AU3309800A (en) |
WO (1) | WO2000057349A1 (en) |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20090295758A1 (en) * | 2008-05-27 | 2009-12-03 | Industrial Technology Research Institute | Method for writing motion and trajectory recognition and writing apparatus and recognizing system |
US20100033352A1 (en) * | 2008-08-08 | 2010-02-11 | Industrial Technology Research Institute | Real-time motion recognition method and inertia-sensing and trajectory-reconstruction device using the same |
EP2469378A2 (en) | 2010-12-23 | 2012-06-27 | Movea | System for inputting graphic elements |
CN104063705A (en) * | 2014-06-05 | 2014-09-24 | 北京捷通华声语音技术有限公司 | Handwriting feature extracting method and device |
EP3061067B1 (en) * | 2013-10-25 | 2023-11-29 | Wacom Co., Ltd. | Dynamic handwriting verification, handwriting-baseduser authentication, handwriting data generation, and handwriting data preservation |
Families Citing this family (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6822639B1 (en) | 1999-05-25 | 2004-11-23 | Silverbrook Research Pty Ltd | System for data transfer |
US6816274B1 (en) * | 1999-05-25 | 2004-11-09 | Silverbrook Research Pty Ltd | Method and system for composition and delivery of electronic mail |
EP1851606A1 (en) * | 2005-02-24 | 2007-11-07 | Nokia Corporation | Motion-input device for a computing terminal and method of its operation |
US7983478B2 (en) | 2007-08-10 | 2011-07-19 | Microsoft Corporation | Hidden markov model based handwriting/calligraphy generation |
US8683582B2 (en) | 2008-06-16 | 2014-03-25 | Qualcomm Incorporated | Method and system for graphical passcode security |
US9501694B2 (en) | 2008-11-24 | 2016-11-22 | Qualcomm Incorporated | Pictorial methods for application selection and activation |
US20130106803A1 (en) * | 2010-07-06 | 2013-05-02 | T-Data Systems (S) Pte Ltd | Data storage device with data input function |
Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US3818443A (en) * | 1972-04-28 | 1974-06-18 | Burroughs Corp | Signature verification by zero-crossing characterization |
US4736445A (en) * | 1986-01-21 | 1988-04-05 | International Business Machines Corporation | Measure of distinguishability for signature verification |
US5577135A (en) * | 1994-03-01 | 1996-11-19 | Apple Computer, Inc. | Handwriting signal processing front-end for handwriting recognizers |
US5768417A (en) * | 1994-09-09 | 1998-06-16 | Motorola, Inc. | Method and system for velocity-based handwriting recognition |
US5781661A (en) * | 1994-06-29 | 1998-07-14 | Nippon Telegraph And Telephone Corporation | Handwritting information detecting method and apparatus detachably holding writing tool |
US5802205A (en) * | 1994-09-09 | 1998-09-01 | Motorola, Inc. | Method and system for lexical processing |
US5854855A (en) * | 1994-09-09 | 1998-12-29 | Motorola, Inc. | Method and system using meta-classes and polynomial discriminant functions for handwriting recognition |
US6335727B1 (en) * | 1993-03-12 | 2002-01-01 | Kabushiki Kaisha Toshiba | Information input device, position information holding device, and position recognizing system including them |
US6556712B1 (en) * | 1996-05-23 | 2003-04-29 | Apple Computer, Inc. | Methods and apparatus for handwriting recognition |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
IL115836A0 (en) * | 1995-10-31 | 1996-01-19 | Baron Tech Ltd | Continuous security system based on motion code |
-
2000
- 2000-03-21 AU AU33098/00A patent/AU3309800A/en not_active Abandoned
- 2000-03-21 WO PCT/GB2000/001052 patent/WO2000057349A1/en not_active Application Discontinuation
- 2000-03-21 EP EP00911105A patent/EP1181665A1/en not_active Withdrawn
- 2000-03-21 US US09/914,262 patent/US7054510B1/en not_active Expired - Fee Related
-
2005
- 2005-10-17 US US11/250,378 patent/US20060088215A1/en not_active Abandoned
Patent Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US3818443A (en) * | 1972-04-28 | 1974-06-18 | Burroughs Corp | Signature verification by zero-crossing characterization |
US4736445A (en) * | 1986-01-21 | 1988-04-05 | International Business Machines Corporation | Measure of distinguishability for signature verification |
US6335727B1 (en) * | 1993-03-12 | 2002-01-01 | Kabushiki Kaisha Toshiba | Information input device, position information holding device, and position recognizing system including them |
US5577135A (en) * | 1994-03-01 | 1996-11-19 | Apple Computer, Inc. | Handwriting signal processing front-end for handwriting recognizers |
US5781661A (en) * | 1994-06-29 | 1998-07-14 | Nippon Telegraph And Telephone Corporation | Handwritting information detecting method and apparatus detachably holding writing tool |
US5768417A (en) * | 1994-09-09 | 1998-06-16 | Motorola, Inc. | Method and system for velocity-based handwriting recognition |
US5802205A (en) * | 1994-09-09 | 1998-09-01 | Motorola, Inc. | Method and system for lexical processing |
US5854855A (en) * | 1994-09-09 | 1998-12-29 | Motorola, Inc. | Method and system using meta-classes and polynomial discriminant functions for handwriting recognition |
US6556712B1 (en) * | 1996-05-23 | 2003-04-29 | Apple Computer, Inc. | Methods and apparatus for handwriting recognition |
Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20090295758A1 (en) * | 2008-05-27 | 2009-12-03 | Industrial Technology Research Institute | Method for writing motion and trajectory recognition and writing apparatus and recognizing system |
US8259092B2 (en) | 2008-05-27 | 2012-09-04 | Industrial Technology Research Institute | Method for writing motion and trajectory recognition and writing apparatus and recognizing system |
US20100033352A1 (en) * | 2008-08-08 | 2010-02-11 | Industrial Technology Research Institute | Real-time motion recognition method and inertia-sensing and trajectory-reconstruction device using the same |
US8229226B2 (en) | 2008-08-08 | 2012-07-24 | Industrial Technology Research Institute | Real-time motion recognition method and inertia-sensing and trajectory-reconstruction device using the same |
EP2469378A2 (en) | 2010-12-23 | 2012-06-27 | Movea | System for inputting graphic elements |
EP3061067B1 (en) * | 2013-10-25 | 2023-11-29 | Wacom Co., Ltd. | Dynamic handwriting verification, handwriting-baseduser authentication, handwriting data generation, and handwriting data preservation |
CN104063705A (en) * | 2014-06-05 | 2014-09-24 | 北京捷通华声语音技术有限公司 | Handwriting feature extracting method and device |
Also Published As
Publication number | Publication date |
---|---|
US7054510B1 (en) | 2006-05-30 |
WO2000057349A1 (en) | 2000-09-28 |
AU3309800A (en) | 2000-10-09 |
EP1181665A1 (en) | 2002-02-27 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US20060088215A1 (en) | Handwriting recognition system | |
US6906703B2 (en) | Electronic module for sensing pen motion | |
JPH0836462A (en) | Hand-writing input device using two or more sensing technologies | |
EP0523066B1 (en) | Handwriting apparatus for information collection based on force and position | |
CN100377043C (en) | Three-dimensional hand-written identification process and system thereof | |
JPH11338626A (en) | Handwriting inputting method, handwriting input system and writing material | |
Yanay et al. | Air-writing recognition using smart-bands | |
CN1530876A (en) | Handwriting path identifying system and method | |
WO1996039677A1 (en) | Method and apparatus for character recognition of hand-written input | |
Baron et al. | Acceleration measurement with an instrumented pen for signature verification and handwriting analysis | |
US6625314B1 (en) | Electronic pen device and character recognition method employing the same | |
Oh et al. | Inertial sensor based recognition of 3-D character gestures with an ensemble classifiers | |
US6330359B1 (en) | Pen-grip type of input apparatus using finger pressure and gravity switches for character recognition | |
KR20120064922A (en) | Method for Finger language recognition using EMG and Gyro sensor and Apparatus thereof | |
CA2022075C (en) | Cross-product filter | |
US20150116285A1 (en) | Method and apparatus for electronic capture of handwriting and drawing | |
Milner | Handwriting recognition using acceleration-based motion detection | |
CN115769177A (en) | System for detecting handwriting problems | |
US9195887B2 (en) | Retrieving apparatus, retrieving method, and computer program product | |
Zhang et al. | Towards an ubiquitous wireless digital writing instrument using MEMS motion sensing technology | |
EP0542557B1 (en) | Systems and methods for handprint recognition acceleration | |
Toyozumi et al. | Trajectory reconstruction algorithm based on sensor fusion between IMU and strain gauge for stand-alone digital pen | |
JP6821174B2 (en) | Handwritten character recognition device, detection device and processing device | |
JPH11296292A (en) | Pen type input device and method for recognizing character | |
Tuncer et al. | Handwriting recognition by derivative dynamic time warping methodology via sensor-based gesture recognition. |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
STCB | Information on status: application discontinuation |
Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION |