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CN100587660C - A method and device for predictive recognition of handwritten characters - Google Patents

A method and device for predictive recognition of handwritten characters Download PDF

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Publication number
CN100587660C
CN100587660C CN200710096215A CN200710096215A CN100587660C CN 100587660 C CN100587660 C CN 100587660C CN 200710096215 A CN200710096215 A CN 200710096215A CN 200710096215 A CN200710096215 A CN 200710096215A CN 100587660 C CN100587660 C CN 100587660C
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character
characters
handwritten
handwriting
recognition
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CN101276249A (en
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王炎
陈又新
罗恒亮
胡洪涛
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Samsung Guangzhou Mobile R&D Center
Samsung Electronics Co Ltd
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Beijing Samsung Telecommunications Technology Research Co Ltd
Samsung Electronics Co Ltd
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Abstract

本发明提供了一种利用预测的方式进行手写字符识别的方法和装置。所述方法包括以下步骤：用户手写输入字符的一定数量的笔迹点；手写字符识别器对所述字符已写入的笔迹点进行识别，得到相应的一组识别结果；利用得到的识别结果信息以及包括在信息预测字符库中的多个预测字符集进行预测识别，得到一组候选字符，并显示所述候选字符，其中，所述信息预测字符库包含用户所用语言中的部分或全部字符，并且所述多个预测字符集中的每一个预测字符集包含与上下文关系信息、字符结构信息和字符部分笔迹点的识别结果信息之一对应关联的多个预测字符。通过所述方法和装置，无需等到预定的等待时间之后才开始识别字符，从而加快了手写输入的速度。

The invention provides a method and device for recognizing handwritten characters in a predictive manner. The method comprises the following steps: a user handwrites a certain number of handwriting points of a character; a handwritten character recognizer recognizes the written handwriting points of the character to obtain a corresponding set of recognition results; using the obtained recognition result information and performing predictive recognition on a plurality of predictive character sets included in the information predictive character library, obtaining a group of candidate characters, and displaying the candidate characters, wherein the information predictive character library contains part or all of the characters in the language used by the user, and Each of the plurality of predicted character sets includes a plurality of predicted characters correspondingly associated with one of context information, character structure information, and recognition result information of handwriting points of characters. With the method and device, it is not necessary to wait for a predetermined waiting time before starting to recognize characters, thereby speeding up the speed of handwriting input.

Description

A kind of method and apparatus of hand-written character prediction identification
Technical field
The present invention relates generally to Handwritten Digits Recognition, specifically, relates to the method and apparatus that a kind of mode of utilizing prediction is carried out Handwritten Digits Recognition.
Background technology
In recent years, it is very universal to utilize digitizer to carry out the input of hand-written character, and these digitizers comprise computing machine, Tablet-PC, PDA, mobile phone of input medias such as having touch-screen or handwriting pad/writing pencil etc.Handwriting recognition technology correspondingly is one of core technology of hand-written inputting method.Hand-written inputting method brings great convenience for people's input character, especially can't be equipped with the equipment of big keyboard for those, and is as mobile phone, Tablet-PC, PDA, all the more so.On the other hand, hand-written inputting method not too can or be inconvenient to use keyboard to carry out the people that literal is imported also for those, as the old man, can not use the people of traditional input method, provide a kind of fast and the efficient character input mode.
The process of handwriting characters generally is: the user is the hand-written character that needs input on digitizer, the Handwritten Digits Recognition device is discerned the character script point that the user write then, with recognition result, promptly a plurality of candidate characters are presented on the screen and select for the user at last.
At present, the hand-written inputting method of portable terminal (as mobile phone) mainly contains the input of two kinds of styles: the one, and the individual character input promptly has only a handwriting area, writes a character at every turn; The 2nd, multiword input promptly has a plurality of handwriting areas or imports in full frame mode, can import a plurality of characters continuously at every turn.The mode that adopts the individual character input is generally based on following two reasons: the one, and the display screen of mobile phone is less, and demonstration and input (touch-screen input) area are less; The 2nd, import in the finger mode from keyboard, be difficult to locate a plurality of input areas.
When adopting the individual character input mode, the input whether definite user of a stand-by period has finished a character must be lifted by setting one by system, and the stand-by period was generally about 0.5 second.That is, write a stroke from the user and picked up counting, if the stand-by period to and the user does not write another stroke again, think that then the user has finished the input of current character, system begin identification.Obviously, this stand-by period has influenced the speed of handwriting input greatly.
In addition, no matter be to adopt individual character input mode or multiword input mode, system generally all is when the user has write all strokes, just begins to discern, this is also in the input speed that has to a certain degree influenced the user, especially under the more situation of stroke.
In order to overcome the above problems, the someone has proposed a kind of method that a stroke is just once discerned that whenever writes, and this method has solved the problem of stand-by period to a certain extent.
Yet, whenever write the method that a stroke just once discerns and also have following shortcoming: require system that enough fast recognition speed is arranged, that is, before the user writes next stroke, must finish the identification that the front has write stroke; Toward contact need the user all strokes of a character all import finish after, can obtain correct recognition result.
Summary of the invention
To be partly articulated other aspect of the present invention and/or advantage in the following description, by describing, it can become clearer, perhaps can understand by implementing the present invention.
According to an aspect of the present invention, provide a kind of mode of utilizing prediction to carry out the method for Handwritten Digits Recognition, said method comprising the steps of: a) person's handwriting of the some of user's handwriting characters point; B) the Handwritten Digits Recognition device is discerned the person's handwriting point that described character has write, obtains corresponding one group of recognition result; C) utilize recognition result information that obtains and a plurality of predicted character set that are included in the information prediction character repertoire to predict identification, obtain one group of candidate characters, and show described candidate characters, wherein, described information prediction character repertoire comprises the part or all of character in the used language of user, and each predicted character set in described a plurality of predicted character set comprises the corresponding related a plurality of prediction characters of one of recognition result information with context information, charcter topology information and character part person's handwriting point.
According to a further aspect in the invention, provide and planted the device that the mode of utilizing prediction is carried out Handwritten Digits Recognition, described device comprises: the handwriting input module receives the hand-written character of user's input, and produces the person's handwriting point of hand-written character; The Handwritten Digits Recognition device, person's handwriting point to the hand-written character that produces from the handwriting input module is discerned, obtain corresponding one group of recognition result, and export the similar value of each recognition result, described similar value is represented the similarity degree of the person's handwriting point of recognition result and hand-written character; The information prediction character repertoire, comprise part or alphabet in the used language of user, and comprise a plurality of predicted character set, each predicted character set in described a plurality of predicted character set comprises the corresponding related a plurality of prediction characters of one of recognition result information with context information, charcter topology information and character part person's handwriting point; The prediction identification module utilizes recognition result information and described a plurality of predicted character set to predict identification, obtains one group of candidate characters; Display module shows the candidate characters that the identification of prediction identification module obtains.
Description of drawings
By the description of embodiment being carried out below in conjunction with accompanying drawing, these and/or other aspect of the present invention and advantage will become clear and be easier to and understand, wherein:
Fig. 1 is the block diagram that carries out the device of Handwritten Digits Recognition according to the mode of the utilization prediction of the embodiment of the invention;
Fig. 2 is the synoptic diagram according to the prediction character repertoire of the embodiment of the invention;
Fig. 3 is the process flow diagram that carries out the method for Handwritten Digits Recognition according to the mode of the utilization prediction of the embodiment of the invention;
Fig. 4 is the example that can use according to the physical platform of the method and apparatus of Handwritten Digits Recognition of the present invention.
Embodiment
Now the embodiment of the invention is described in detail, its example shown in the accompanying drawings, wherein, identical label is represented same parts all the time.Below with reference to the accompanying drawings embodiment is described to explain the present invention.
Fig. 1 is the block diagram that carries out the device of Handwritten Digits Recognition according to the mode of the utilization prediction of the embodiment of the invention.With reference to figure 1, the device that carries out Handwritten Digits Recognition according to the mode of the utilization of embodiment of the invention prediction comprises handwriting input module 100, Handwritten Digits Recognition device 110, prediction character repertoire 120, prediction identification module 130 and display module 140.
Handwriting input module 100 refers to the device that is used to collect relevant informations such as user's hand-written character person's handwriting, for example electronics board/writing pencil, touch-screen etc.When the user with writing pencil or finger on these devices during handwriting characters, handwriting input module 100 just can obtain the information such as person's handwriting point coordinate, pressure and time parameter of the character imported, wherein, the person's handwriting point of described character can be the person's handwriting point that obtains by the certain hour interval sampling, the person's handwriting point that one or more stroke comprised, perhaps the person's handwriting point of prior set point number.These information are sent to Handwritten Digits Recognition device 110 and handle and discern.
Handwritten Digits Recognition device 110 is the devices that are used for discerning hand-written character, and it exports a plurality of recognition result candidate characters from the information such as person's handwriting point coordinate of the character of handwriting input module 100 reception user inputs.The candidate characters of these outputs generally sorts by itself and this hand-written character similarity degree, the similar more front more that comes.Handwritten Digits Recognition device 110 is also exported the distance value of each candidate characters simultaneously except can exporting the recognition result candidate characters.Distance value is exactly numerical value---the similar value of expression recognition result candidate characters and this hand-written character similarity degree.Similar value is more little, and the expression candidate characters is similar more to this hand-written character.For example, when the user on handwriting input module 100 during handwriting characters " word ", 10 possible recognition result candidate characters of Handwritten Digits Recognition device 110 output are: " word space enjoy Zijia keep to inspire confidence in learn the comet ancestor ", export the similar value of 10 correspondences simultaneously: 6324,9915,10527,10597,11008,11111,11263,11392,11421,11460.
Prediction character repertoire 120 is meant some customizing messages by the character that utilizes input, predicts the character repertoire of the character set that is associated with this character.Character set comprises a plurality of characters that are associated with some customizing messages of the character of importing.With reference to figure 2, prediction character repertoire 120 can be divided at least: association's prediction character repertoire 121, stroke prediction character repertoire 122, radicals by which characters are arranged in traditional Chinese dictionaries prediction character repertoire 123 and local prediction character repertoire 124.
Association prediction character repertoire 121 is meant a character can having imported according to the user, the character repertoire of the predicted character set that output is associated with this symbol.Association prediction character repertoire 121 comprises part or alphabet in the used language of user, and each character all related one group of character that has context relation with this character, described one group of character constitutes associates predicted character set.Context relation used herein comprises word relation, Chinese idiom relation, the constituent relation of word/alphabetic writing and the front and back neighbouring relations of the character that the user once imported etc.Association prediction character repertoire 121 can utilize the front and back neighbouring relations of the character that the user once imported to bring in constant renewal in correction.As example, table 1 has provided a Chinese association prediction character repertoire.
Table 1
Figure C20071009621500081
Figure C20071009621500091
As can be seen from Table 1, association's predicted character set of forming by tens (in the table 1 being 30) characters that each character is all related.The character of sequence number 5 in the table 1 " zhang ", form the word relation respectively with preceding 3 characters in the association predicted character set, i.e. " husband ", " father-in-law ", " measuring ", and do not form word with remaining 27 character.These 27 characters are high words of frequency of utilization in the Chinese character, are used for the quantity of character in association's predicted character set is supplied.This be because do not have again other can follow " zhang " back forms the character of word.The character of sequence number 9 " Ji " in the table 1 because there is not to follow the character of forming word in its back, so relevant character all be to use the high Chinese character of frequency.In addition, for the application on mobile phone, association's prediction character repertoire 121 can directly be obtained from the language library of T9 input method.
Stroke prediction character repertoire 122 is meant one or more strokes and the precedence thereof that can import according to the user, the character repertoire of the predicted character set that output is associated with it.That is to say, given one or more strokes, the prediction character repertoire can provide beginning stroke all characters identical with these one or more strokes.That the stroke that the Chinese information processing system kind is used can be divided into is horizontal, vertical, 5 kinds of left-falling strokes, right-falling stroke, folding etc.As example, table 2 has provided a Chinese stroke prediction character repertoire.As can be seen from Table 2, each organize orderly stroke all related a predicted character set of forming by a plurality of characters.
Table 2
Figure C20071009621500101
Figure C20071009621500111
Radicals by which characters are arranged in traditional Chinese dictionaries predictions character repertoire 123 is meant the character radicals by which characters are arranged in traditional Chinese dictionaries (that is, radical is the part of character) that can import according to the user, and output is the character repertoire of the predicted character set of beginning with these radicals by which characters are arranged in traditional Chinese dictionaries.For example, the user imports radicals by which characters are arranged in traditional Chinese dictionaries " Lv ", and then Dui Ying predicted character set is " skill Ai Jie is the Chinese herbaceous peony awns sesame bud that rues altogether ... ".As example, table 3 has provided a Chinese radicals by which characters are arranged in traditional Chinese dictionaries prediction character repertoire.As can be seen from Table 3, predicted character set of forming by a plurality of characters that each radicals by which characters are arranged in traditional Chinese dictionaries is all related.
Table 3
Figure C20071009621500121
Local prediction character repertoire 124 is meant the part (may be some strokes, also may be the combination of radicals by which characters are arranged in traditional Chinese dictionaries and stroke) of the character that can import according to the user, output and these character repertoires of the similar predicted character set in importation.For example, user's handwriting input Then Dui Ying predicted character set is " state group is with being stranded the intercalation circle of child's order because of day ".
Usually, association prediction character repertoire 121, stroke prediction character repertoire 122 and radicals by which characters are arranged in traditional Chinese dictionaries prediction character repertoire 123 are set up in advance, and local prediction character repertoire 124 then is according to the identification of handwriting characters is provided in real time by Character recognizer 110.
In addition, the present invention is applicable to the identification of multilingual character, as Chinese, numeral, English, Japanese, Korean etc.Corresponding prediction character repertoire also has multiple, as Chinese prediction character repertoire, English prediction character repertoire, Japanese prediction character repertoire, Korean prediction character repertoire etc.Prediction character repertoire 120 comprises the part or all of character in the used language of user.
Prediction identification module 130 receives from a plurality of recognition result candidate characters of Handwritten Digits Recognition device 110 outputs and from predicting the predicted character set of character repertoire 120 outputs, and the person's handwriting point of current input is predicted identification.Particularly, the previous character that utilizes the user to import exactly, and the part person's handwriting point of current input, according to the recognition result of current input person's handwriting point, it is the predicted character set of stroke, radicals by which characters are arranged in traditional Chinese dictionaries or local recognition result correspondence, the prediction person's handwriting point that the active user imported may be any character, and exports in the mode of candidate result.Then, the recognition result candidate characters that obtains is discerned in 130 predictions of output of prediction identification module.
Display module 140 is used for showing the recognition result candidate characters of prediction identification module 130 outputs, selects to offer the user.
With reference to Fig. 3 the method that the mode of predicting according to the utilization of the embodiment of the invention is carried out Handwritten Digits Recognition is described below.
Fig. 3 is the process flow diagram that carries out the method for Handwritten Digits Recognition according to the mode of the utilization prediction of the embodiment of the invention.With reference to figure 3, in step 301, the person's handwriting point of user's handwriting characters on handwriting input module 100.In step 302, calculate since the identification of last time, if the person's handwriting point of user's input reaches certain quantity, then carry out step 303, otherwise return step 301.For example, can set the user and whenever write a stroke, system just discerns once.In step 303, the part or all of person's handwriting point that 110 couples of users of Handwritten Digits Recognition device have imported is discerned, and exports the similar value of a plurality of recognition result candidate characters and each candidate characters correspondence.In step 304, from the recognition result of step 303, obtain stroke, the radicals by which characters are arranged in traditional Chinese dictionaries of current input, obtain the local recognition result (promptly all have been imported person's handwriting and have put pairing recognition result) and a last character of having imported of current character simultaneously.In step 305, from the prediction character repertoire of having set up, take out and discern the stroke that obtains, radicals by which characters are arranged in traditional Chinese dictionaries and a last corresponding predicted character set of input character.In step 306, prediction identification module 130 is predicted identification, obtains the preferred recognition result candidate characters of the current person's handwriting point of having imported.The method of prediction identification will further describe below.In step 307, display module 140 is shown to the user with current recognition result candidate characters, so that the user selects.In step 308, if the user finds and select required character from current candidate characters, then finish the input of this character, carry out step 311; Otherwise carry out step 309.In step 309,, show that then the user has write all person's handwritings of current character, carry out step 310 if a stand-by period of lifting of default arrives; Otherwise, show that the user has not also write current character, then return step 301 and continue handwriting characters to allow the user.Wherein, in step 310, system can obtain all complete person's handwritings of current character, carries out general handwriting recognition process.In step 311,, then return step 301 if the user also needs the handwriting input character late; Otherwise input process finishes.
Following mask body introduction is according to recognition methods and the pre-detection identifying method to stroke and radicals by which characters are arranged in traditional Chinese dictionaries of the present invention.
In step 303, to horizontal, vertical, cast aside, press down, the recognition methods of 5 strokes of folding is as described below: the user being started to write each time and lift person's handwriting point between the pen is input to Character recognizer 110 and discerns, if first-selected recognition result is that (similar value is more little less than a certain threshold value T1 for the similar value of one of these 5 strokes and first-selected recognition result correspondence, the confidence level of expression recognition result is high more), think that then the person's handwriting point of current input is the stroke of first-selected recognition result correspondence.Recognition methods to radicals by which characters are arranged in traditional Chinese dictionaries is as described below: all person's handwriting points that the user has been imported are input to Character recognizer 110 and discern, if first-selected recognition result is that (similar value is more little less than a certain threshold value T1 for the similar value of one of radicals by which characters are arranged in traditional Chinese dictionaries and first-selected recognition result correspondence, the confidence level of expression candidate characters is high more), think that then the person's handwriting point of current input is the radicals by which characters are arranged in traditional Chinese dictionaries of first-selected recognition result correspondence.
A kind of preferred pre-detection identifying method that adopts in the step 306 is described below.That is, the stroke predicted character set of taking out in step 305 is A, and the radicals by which characters are arranged in traditional Chinese dictionaries predicted character set is B, and association's predicted character set is C, and the part identification candidate result corresponding characters collection in the step 304 is D.If do not identify stroke, then A is empty, does not identify radicals by which characters are arranged in traditional Chinese dictionaries, and then B is empty, and a last character does not exist, and then C is empty, after current all the person's handwriting point that has write identifications, does not discern candidate result, and then D is empty.Define orderly Candidate Set E, F, G simultaneously.Like this, the method for prediction identification can be described as:
1. if A and B are empty, then E is empty;
2. if A non-NULL, B are empty, then E=A;
If 3. A sky, B non-NULL, then E=B;
If 4. A and B non-NULL all, and common factor is arranged, then E=B, and the ordering among the E is preferential with the common factor;
5. if A and B non-NULL all, and do not have common factor, then E=B
6. if E and C are empty, then F is empty;
7. if E non-NULL, C are empty, then F=E;
If 8. E sky, C non-NULL, then F=C;
If 9. E and C non-NULL all, and common factor is arranged, then F=E, and the ordering among the F is preferential with the common factor;
10. if E and C non-NULL all, and do not have common factor, then F=E;
11. if F and D are empty, then G is empty;
12. if the F non-NULL, D is empty, then G=F;
If 13. the F sky, D non-NULL, then G=D;
If 14. F and D non-NULL all, and common factor is arranged, then G=F, and the ordering among the G is preferential with the common factor;
15. if F and D non-NULL all and does not have common factor, G=F then;
16. prediction of output recognition result G.
Be that example is described identifying in detail with " not " word in user's input " identification " below.Suppose that before this " knowledge " word has been imported and finished.Detailed identification step is as follows.
The 1st step: the user is handwriting input the first stroke on handwriting input module 100
Figure C20071009621500141
The 2nd step: current is a stroke (pen of starting to write and lift), carry out step 303.The 3rd step: 110 pairs of Handwritten Digits Recognition devices
Figure C20071009621500142
Discern, obtain first-selected recognition result and be perpendicular " Shu ", and similar value=3200.The 4th step: similar value 3200 is less than preset threshold T1=5000, and promptly recognition result is stroke perpendicular " Shu ", local recognition result be " Shu ' the 11i fore-telling! V w r ", and local recognition result does not have corresponding radicals by which characters are arranged in traditional Chinese dictionaries.The 5th step: from the prediction character repertoire of having set up, take out " Shu " corresponding predicted character set " only see little day in when going up state in being work as back herewith a little bright because of listening most the interior other water of four-hole ... ", predicted character set be " malapropism must be seen broken to fractal boundary it ... " in a last association that input character " knowledge " is corresponding, at this moment local recognition result be " Shu ' the 11i fore-telling! V w r ".The 6th step: predict identification, the current preferred recognition result candidate characters of having imported person's handwriting point for " only see little day in when going up state in not being work as back herewith a little bright because of listening most the interior water of four-hole ....The 7th step: above recognition result candidate characters is shown to the user so that the user selects by display module 140.The 8th step: the user does not select from candidate characters, but continues to write the 2nd:
Figure C20071009621500143
(annotate: the user can obtain correct recognition result in this step).The 9th step: 110 pairs the 2nd of Handwritten Digits Recognition device
Figure C20071009621500151
Discern, obtaining first-selected recognition result is Zhe “ Ya ", and similar value=3556, and the person's handwriting point imported of 110 pairs of Handwritten Digits Recognition devices
Figure C20071009621500152
Discern, obtain local recognition result and be " mouthful day several R2 say Z river district P ", and similar value=2011 of first-selected recognition result " mouth ".The 10th step: first-selected recognition result Zhe “ Ya " similar value 3556 is less than preset threshold T1=5000; therefore the 2nd recognition result is stroke Zhe “ Ya ", the similar value 2011 of first-selected recognition result " mouth " is less than setting threshold T2=5000 simultaneously, and therefore the importation is radicals by which characters are arranged in traditional Chinese dictionaries " mouths ".The 11st step: from the prediction character repertoire of having set up, take out preceding 2 for " Shu Ya " corresponding predicted character set " when mouthful day being China in the order Tian Yue say and the dawn socket of the eye is looked up with eyes wide open eyeball and stared at that late at night drought is prosperous finely sees peaceful sleepy socket of the eye and take aim to hide and look sidelong at tool and look at ... "; the predicted character set that radicals by which characters are arranged in traditional Chinese dictionaries " mouth " are corresponding " a mouthful medium size sting porphin only a history brother sound of a bird chirping rebuke to sigh to hold in the month and do not cry ... "; and last association's predicted character set that input character " knowledge " is corresponding " malapropism must be seen brokenly to fractal boundary it ... ", this moment, local recognition result was " mouthful day several R2 say Z river district P "; The 12nd step: predict identification, the current preferred recognition result candidate characters of having imported person's handwriting point for " do not see that boundary's mouth medium size stings porphin a history brother sound of a bird chirping and rebuke to sigh to hold in the month and cry ....The 13rd step: above recognition result candidate characters is shown to the user so that the user selects by display module 140.The 14th step: the user does not select from candidate characters, but continues to write the 3rd
Figure C20071009621500153
(annotate: the user can obtain correct recognition result in this step).The 15th step: 110 pairs the 3rd of Handwritten Digits Recognition device
Figure C20071009621500154
Discern, recognition result does not have stroke, and the person's handwriting point imported of 110 pairs of Handwritten Digits Recognition devices
Figure C20071009621500155
Discern, obtain local recognition result for " other merit cut to pieces cut before the letter an ancient unit of weight encourage draw row ", and local recognition result does not have corresponding radicals by which characters are arranged in traditional Chinese dictionaries.The 16th step: from the prediction character repertoire of having set up, take out preceding two for " Shu Ya " corresponding predicted character set " when mouthful day being China in the order Tian Yue say and the dawn socket of the eye is looked up with eyes wide open eyeball and stared at that late at night drought is prosperous finely sees peaceful sleepy socket of the eye and take aim to hide and look sidelong at tool and look at ... "; the predicted character set that radicals by which characters are arranged in traditional Chinese dictionaries " mouth " are corresponding " a mouthful medium size sting porphin only a history brother sound of a bird chirping rebuke to sigh to hold in the month and do not cry ... "; and last association's predicted character set that input character " knowledge " is corresponding " malapropism must be seen brokenly to fractal boundary it ... ", this moment local recognition result for " other merit cut to pieces cut before the letter an ancient unit of weight encourage draw row ".The 17th step: predict identification, the current preferred recognition result candidate characters of having imported person's handwriting point for " other merit is cut a mouthful medium size to pieces and is stung porphin a history brother sound of a bird chirping and rebuke to sigh to hold in the month and cry ....The 18th step: above recognition result candidate characters is shown to the user so that the user selects by display module 140.The 19th step: the user does not select from candidate characters, but continues to write last 1
Figure C20071009621500156
(annotate: the user can obtain correct recognition result in this step).The 20th step: owing to when writing one, do not have stroke and radicals by which characters are arranged in traditional Chinese dictionaries in the recognition result, so no longer discern stroke and radicals by which characters are arranged in traditional Chinese dictionaries in this step, Handwritten Digits Recognition device 110 is the person's handwriting point to having imported only Discern, local recognition result is " do not cut to pieces declare ice-cold chaste tree row Yan encourage to cut cut ".The 21st step: from the prediction character repertoire of having set up, take out preceding two for " Shu Ya " corresponding predicted character set " when mouthful day being China in the order Tian Yue say and the dawn socket of the eye is looked up with eyes wide open eyeball and stared at that late at night drought is prosperous finely sees peaceful sleepy socket of the eye and take aim to hide and look sidelong at tool and look at ... "; " a mouthful medium size is stung porphin a history brother sound of a bird chirping and is rebuked to sigh to hold in the month and do not cry to take out the corresponding predicted character set of radicals by which characters are arranged in traditional Chinese dictionaries " mouth " ... "; and last association's predicted character set that input character " knowledge " is corresponding " malapropism must be seen brokenly to fractal boundary it ... ", local recognition result this moment " do not cut to pieces declare ice-cold chaste tree row Yan encourage to cut cut ".The 22nd step: predict identification, the current preferred recognition result candidate characters of having imported person's handwriting point for " not cutting a mouthful medium size to pieces stings porphin a history brother sound of a bird chirping and rebukes to sigh to hold in the month and cry ....The 23rd step: above recognition result candidate characters is shown to the user so that the user selects by display module 140.The 24th step: the user does not select from candidate characters, but waits the predetermined stand-by period arrival (annotate: the user can obtain correct recognition result in this step) of (stand-by period that word has been write that is default).The 25th step: after predetermined past stand-by period, the person's handwriting point that 110 pairs of Handwritten Digits Recognition devices have been imported
Figure C20071009621500161
Carry out general identification, obtain recognition result and be " do not cut to pieces declare ice-cold chaste tree row Yan encourage to cut cut ".In the 26th step, the user selects first candidate " not ", finishes this word input.
Also can see from above step, use the method for carrying out Handwritten Digits Recognition according to the mode of utilization prediction of the present invention, the user can obtain " not " word of required input in the 8th step.And according to general recognition methods, then need to go on foot " not " word that the user can obtain required input to the 26th.
The method and apparatus that carries out Handwritten Digits Recognition according to the mode of utilization prediction of the present invention has favorable expansibility and ease for use, be suitable for equipment such as Tablet-PC, PDA and hand-written mobile phone and use, be particularly suitable for that this computing power of mobile phone is weak, the terminal of limited storage space.The method and apparatus that carries out Handwritten Digits Recognition according to the mode of utilization prediction of the present invention can be widely used in the various mobile terminal devices that can carry out handwriting input, also can be applied to the equipment that computing power is arranged of external recording device, such as the PC system 400 among Fig. 4, PDA 401, mobile phone 402 and flat computer 403 etc.
By using the method and apparatus that carries out Handwritten Digits Recognition according to the mode of utilization prediction of the present invention, when the user carries out handwriting input, as long as the part of a character of input just can obtain the correct recognition result of this character immediately, thereby can select to finish the input of this character.Therefore need not just to begin identification character after stand-by period of default by the time, thereby accelerated the speed of handwriting input.
Though specifically shown and described the present invention with reference to exemplary embodiment of the present invention, but it should be understood by one skilled in the art that, under the situation that does not break away from the spirit and scope of the present invention that are defined by the claims, can carry out various changes to these embodiment in form and details.

Claims (19)

1、一种利用预测的方式进行手写字符识别的方法，所述方法包括以下步骤：1. A method for handwritten character recognition in a predictive manner, said method comprising the following steps: a)用户手写输入字符的一定数量的笔迹点；a) A certain number of handwriting points of the user's handwritten input character; b)手写字符识别器对所述字符已写入的笔迹点进行识别，得到相应的一组识别结果；b) the handwritten character recognizer recognizes the written handwriting points of the characters, and obtains a corresponding group of recognition results; c)利用得到的识别结果信息以及包括在信息预测字符库中的多个预测字符集进行预测识别，得到一组候选字符，并显示所述候选字符，c) performing predictive recognition using the obtained recognition result information and a plurality of predictive character sets included in the information predictive character library to obtain a group of candidate characters, and displaying the candidate characters, 其中，所述信息预测字符库包含用户所用语言中的部分或全部字符，并且所述多个预测字符集中的每一个预测字符集包含与上一字符的上下文关系信息、字符结构信息和字符已写入的笔迹点的识别结果信息之一对应关联的多个预测字符。Wherein, the information predicted character library includes some or all characters in the language used by the user, and each predicted character set in the plurality of predicted character sets includes contextual relationship information with the previous character, character structure information and character written One of the recognition result information of the entered handwriting point corresponds to a plurality of associated predicted characters. 2、如权利要求1所述的手写字符识别的方法，还包括以下步骤：2. The method for handwritten character recognition as claimed in claim 1, further comprising the steps of: d)如果所述字符的输入尚未完毕，则允许用户继续手写输入所述字符的一定数量的笔迹点；d) If the input of the character has not been completed, the user is allowed to continue handwriting a certain number of handwriting points of the character; e)如果所述字符的输入已经完毕，则在预定的等待时间之后，手写字符识别器对所有属于所述字符的笔迹点进行识别，得到一组候选字符并显示所述候选字符。e) If the input of the character has been completed, after a predetermined waiting time, the handwritten character recognizer recognizes all handwriting points belonging to the character, obtains a group of candidate characters and displays the candidate characters. 3、如权利要求1所述的手写字符识别的方法，其中，所述字符结构信息包括字符笔划及其次序信息和字符部首信息。3. The method for handwritten character recognition according to claim 1, wherein said character structure information includes character strokes and their sequence information and character radical information. 4、如权利要求1所述的手写字符识别的方法，其中，所述多个预测字符集分为基于字符结构信息的预测字符集、基于对字符已写入的笔迹点的识别结果信息得到的预测字符集和基于上一字符的上下文关系信息的预测字符集。4. The method for handwritten character recognition as claimed in claim 1, wherein said plurality of predicted character sets are divided into predicted character sets based on character structure information, and those obtained based on recognition result information of handwriting points that characters have been written into. A predicted character set and a predicted character set based on the context information of the previous character. 5、如权利要求4所述的手写字符识别的方法，其中，所述基于字符结构信息的预测字符集分为基于输入的字符笔划及其次序的笔划预测字符集以及基于字符部首的部首预测字符集。5. The method for handwritten character recognition according to claim 4, wherein the predicted character set based on character structure information is divided into a stroke predicted character set based on input character strokes and their order, and a radical based on character radicals Predicted character set. 6、如权利要求5所述的手写字符识别的方法，其中，所述笔划在中文系统中分为横、竖、撇、捺、折等5种。6. The method for recognizing handwritten characters as claimed in claim 5, wherein the strokes in the Chinese system are divided into five types: horizontal, vertical, left, right, and folded. 7、如权利要求4所述的手写字符识别的方法，其中，所述上下文关系包括词语关系、成语关系、单词/拼音文字的构成关系、以及用户曾经输入过的字符的前后相邻关系。7. The method for handwritten character recognition as claimed in claim 4, wherein the contextual relationship includes word relationship, idiom relationship, word/pinyin composition relationship, and front and rear adjacency relationship of characters input by the user. 8、如权利要求1所述的手写字符识别的方法，其中，所述字符的笔迹点是根据以下方式得到的笔迹点中的一种，即：通过一定时间间隔采样获得的笔迹点；一个或多个笔划所包含的笔迹点；事先设定点数的笔迹点。8. The method for handwritten character recognition as claimed in claim 1, wherein the handwriting point of the character is one of the handwriting points obtained in the following manner, that is: the handwriting points obtained by sampling at a certain time interval; one or The handwriting points included in multiple strokes; the handwriting points with the number of points set in advance. 9、如权利要求1所述的手写字符识别的方法，其中，在所述预测识别的步骤中，将多个预测字符集中都存在的字符作为所述一组候选字符中的首选字符进行显示。9. The method for handwritten character recognition as claimed in claim 1, wherein, in the step of predictive recognition, characters existing in multiple predictive character sets are displayed as preferred characters in the group of candidate characters. 10、一种利用预测的方式进行手写字符识别的装置，所述装置包括：10. A device for recognizing handwritten characters in a predictive manner, the device comprising: 手写输入模块，接收用户输入的手写字符，并产生手写字符的笔迹点；The handwriting input module receives the handwritten characters input by the user and generates handwriting points of the handwritten characters; 手写字符识别器，对从手写输入模块产生的手写字符的笔迹点进行识别，得到相应的一组识别结果，并输出每个识别结果的相似值，所述相似值表示识别结果与手写字符的笔迹点的相似程度；The handwritten character recognizer recognizes the handwriting points of the handwritten characters generated by the handwriting input module, obtains a corresponding set of recognition results, and outputs the similarity value of each recognition result, and the similarity value indicates that the recognition result and the handwriting of the handwritten character point similarity; 信息预测字符库，包含用户所用语言中部分或全部字符，并且包括多个预测字符集，所述多个预测字符集中的每个预测字符集包含与上一字符的上下文关系信息、字符结构信息和字符已写入的笔迹点的识别结果信息之一对应关联的多个预测字符；The information predictive character library contains part or all of the characters in the language used by the user, and includes multiple predictive character sets, and each predictive character set in the multiple predictive character sets contains contextual relationship information with the previous character, character structure information and One of the recognition result information of the handwriting point where the character has been written corresponds to a plurality of associated predicted characters; 预测识别模块，利用识别结果信息以及所述多个预测字符集进行预测识别，得到一组候选字符；The predictive recognition module uses the recognition result information and the plurality of predictive character sets to perform predictive recognition to obtain a set of candidate characters; 显示模块，显示预测识别模块识别得到的候选字符。The display module displays the candidate characters recognized by the predictive recognition module. 11、如权利要求10所述的手写字符识别的装置，其中，所述字符结构信息包括字符笔划及其次序信息和字符部首信息。11. The device for recognizing handwritten characters according to claim 10, wherein said character structure information includes character strokes and their sequence information and character radical information. 12、如权利要求10所述的手写字符识别的装置，其中，如果用户输入的手写字符尚未书写完毕，则手写输入模块继续接收所述手写字符，并产生相应的笔迹点。12. The device for recognizing handwritten characters as claimed in claim 10, wherein if the handwritten characters input by the user have not been completely written, the handwriting input module continues to receive the handwritten characters and generate corresponding handwriting points. 13、如权利要求10所述的手写字符识别的装置，其中，如果用户完成所述手写字符的输入，则在预定的等待时间之后，手写字符识别器对所有属于所述手写字符的笔迹点进行识别，得到一组候选字符。13. The device for handwritten character recognition as claimed in claim 10, wherein, if the user completes the input of the handwritten character, after a predetermined waiting time, the handwritten character recognizer performs a check on all handwriting points belonging to the handwritten character Identify and get a set of candidate characters. 14、如权利要求10所述的手写字符识别的装置，其中，所述多个预测字符集分为基于字符结构信息的预测字符集、基于对字符已写入的笔迹点的识别结果信息得到的预测字符集和基于上一字符的上下文关系信息的预测字符集。14. The device for handwritten character recognition according to claim 10, wherein the plurality of predicted character sets are divided into predicted character sets based on character structure information, and those obtained based on recognition result information of handwriting points that have been written into characters. A predicted character set and a predicted character set based on the context information of the previous character. 15、如权利要求14所述的手写字符识别的装置，其中，所述基于字符结构信息的预测字符集分为基于输入的字符笔划及其次序的笔划预测字符集以及基于字符部首的部首预测字符集。15. The device for handwritten character recognition according to claim 14, wherein the predicted character set based on character structure information is divided into a stroke predicted character set based on input character strokes and their order, and a radical based on character radicals Predicted character set. 16、如权利要求15所述的手写字符识别的装置，其中，所述笔划在中文系统中分为横、竖、撇、捺、折等5种。16. The handwritten character recognition device according to claim 15, wherein the strokes in the Chinese system are divided into five types: horizontal, vertical, left, right, and folded. 17、如权利要求14所述的手写字符识别的装置，其中，所述上下文关系包括词语关系、成语关系、单词/拼音文字的构成关系、以及用户曾经输入过的字符的前后相邻关系。17. The device for handwritten character recognition according to claim 14, wherein the contextual relationship includes word relationship, idiom relationship, composition relationship of words/pinyin characters, and front and rear adjacency relationship of characters previously input by the user. 18、如权利要求10所述的手写字符识别的装置，其中，所述手写字符的笔迹点是根据以下方式产生的笔迹点中的一种，即：通过一定时间间隔采样获得的笔迹点；一个或多个笔划所包含的笔迹点；事先设定点数的笔迹点。18. The device for handwritten character recognition as claimed in claim 10, wherein the handwriting point of the handwritten character is one of the handwriting points generated in the following manner, that is: handwriting points obtained by sampling at a certain time interval; or the handwriting points contained in multiple strokes; the handwriting points with the number of points set in advance. 19、如权利要求10所述的手写字符识别的装置，其中，预测识别模块将多个预测字符集中都存在的字符确定为所述一组候选字符中的首选字符。19. The device for recognizing handwritten characters as claimed in claim 10, wherein the predictive recognition module determines a character existing in a plurality of predicted character sets as a preferred character in the group of candidate characters.
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