CN102750555B - Expression identification device applied to instant messaging tool - Google Patents
Expression identification device applied to instant messaging tool Download PDFInfo
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- CN102750555B CN102750555B CN201210224496.1A CN201210224496A CN102750555B CN 102750555 B CN102750555 B CN 102750555B CN 201210224496 A CN201210224496 A CN 201210224496A CN 102750555 B CN102750555 B CN 102750555B
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Abstract
The invention discloses an expression robot applied to an instant messaging tool. The expression robot can recognize expression marks used by users in real time and can make same responses as the meaning represented by the expression marks. In addition, an expression recognizing method overcomes the defects that the complexity degree is high, the real-time performance is poor, and a secret key needs to be decoded again after the instant messaging tool is updated. In a system, a chat window monitoring module intercepts chat window images as pictures and stores the pictures when the instant messaging tool has new chat message display, or the chat window monitoring module regularly is timed to intercept the chat window images as pictures and to store the pictures; an expression mark positioning module finds expression marks in the intercepted pictures, and the positions of the expression marks are sent to an expression mark recognizing module; the expression mark recognizing module comprises the positions of the expression marks and expression marks in the existing expression mark bank, and the meanings of the expression marks are determined and are sent to a response module; and the response module makes responses in set expression modes after receiving results sent by the expression mark recognizing module.
Description
Technical field
The present invention is a kind of expression recognition apparatus based on immediate communication tool, is specifically related to screen capture, image identification technical field.
Background technology
Immediate communication tool is also called instant messenger, is a kind of service based on the Internet, through the development of more than ten years, has nowadays had a large amount of fixed-line subscribers, has penetrated into the every aspect in our live and work.Emoticon is born in the Internet, is a kind of network subculture originally, but developing rapidly and popularizing along with network, it obtains accepting extensively of people.
General immediate communication tool all has the function inserting emoticon, greatly facilitates the expression of user, enhances and exchanges enjoyment and Consumer's Experience.At present, emoticon is mainly towards more polynary, and more lively and complicated future development, the present invention proposes a creationary road for development: allow emoticon actualization more.The program can be monitored the window interface of immediate communication tool, then identifies the implication of the emoticon that user uses, and makes the response meeting this emoticon implication for the emoticon be identified.The emoticon used in chat process can be experienced more intuitively by expression recognition apparatus user, increase experience sense and the enjoyment of instant communication user thus.This is the product of a novelty, rarely has the reference to forefathers' experience.
When carrying out the design of emoticon identifying schemes, first it is envisioned that analysis being decrypted to the packet of immediate communication tool transmission, therefrom extracting the code of emoticon, thus realize identifying.But current immediate communication tool all can carry out very complicated encryption to it in the transport process of chat content; decode key and need the long time; difficulty is larger; and immediate communication tool usually can irregular upgrading; each upgrading all can reset key; therefore immediate communication tool upgrading after need the defect again decoding key, these needs just bringing the program constantly decode key defect, complexity is high, real-time is not good, thus cannot batch production and popularization.
Summary of the invention
In view of this, the invention provides a kind of expression recognition apparatus based on immediate communication tool, it can identify the emoticon that user uses in real time, and makes the response the same with implication representated by this emoticon.And, its expression recognition method not adopts the method packet of immediate communication tool transmission being decrypted to analysis, avoids the defect that the complexity adopting this scheme to bring is high, real-time is not good, immediate communication tool needs again to decode key after upgrading.
The method is achieved in that
This is based on the expression recognition apparatus of immediate communication tool, and it comprises chat window monitoring modular, emoticon locating module, emoticon identification module and respond module;
Described chat window monitoring modular, for after determining that current focus window is the chat window of immediate communication tool, described chat window is monitored, timing or when user has new chat messages to show, the image interception of chat window is got off, and saves as picture;
Described emoticon locating module, for analyze chat window monitoring modular intercept the picture got off, find emoticon wherein, after finding emoticon, the position of emoticon sent to described emoticon identification module;
Described emoticon identification module, for when behind the position receiving the emoticon that emoticon locating module sends, emoticon in the emoticon of this position and known emoticon storehouse is contrasted, thus determine the meaning representated by this emoticon, then result is sent to respond module;
Described respond module, for after receiving the result that emoticon identification module sends over, is responded by the technique of expression of setting;
Further, described emoticon locating module comprises cutting module, gray processing module, Leveling Block and Hough Hough detection module:
Cutting module, for according to the position of dialog boxes in chat window, cuts out the image of dialog boxes, the image cut out is sent to gray processing module from the image of chat window;
Gray processing module, for received image is carried out gray processing out, obtains gray-scale map, sends to Leveling Block;
Leveling Block, for carrying out Gaussian smoothing to the gray-scale map received;
Hough detection module, for carrying out Hough transform to the image after Gaussian smoothing, detects the position at circular emoticon place; Only exporting coordinate x, y in the emoticon identified is all the position of maximum emoticon; Wherein x-axis, y-axis with the upper left corner of dialog boxes for zero point;
Wherein, the Hough transform of described Hough detection module is from the lower right corner of dialog boxes, and according to from right to left, order computation from bottom to up, when first bowlder being detected, exports home position, and stops detecting;
Further, described emoticon identification module comprises extraction module, matching module and identification module;
Described extraction module, for the position exported according to emoticon locating module, obtains emoticon image the image of the described dialog boxes obtained from cutting module, sends to matching module;
Described matching module, for using received emoticon image as template, using the image comprising all acquiescence emoticons that prestores as global image, then carry out template matches, finally find out the position of emoticon image in global image;
Identification module in described emoticon identification module, for according to the position range of acquiescence emoticon each in known global image and expression meanings, judge the position of the emoticon image that described matching module is found out which expression meanings corresponding, expression meanings is sent to respond module.
Further, described respond module is responded by sound, image and/or action.
Beneficial effect:
The invention provides a kind of expression recognition apparatus being applied to immediate communication tool, the emoticon that user uses can be identified in real time, and make the response the same with implication representated by this emoticon, and the more important thing is, the expression recognition method of this expression and people thereof not adopts the method packet of immediate communication tool transmission being decrypted to analysis, do not need again to decode key after immediate communication tool upgrading, therefore versatility is good, is applicable to various immediate communication tool.And the method relies on sectional drawing to carry out Expression Recognition, method is simple, can, by a lot of existing image processing method, implement very simple, and amount of calculation be also little, thus be conducive to the real-time improving Expression Recognition.
Secondly, multiple circle being positioned at diverse location may be obtained after Hough loop truss, here only export the position of the maximum circle of x, y according to the feature of immediate communication tool, thus avoiding multiple round position, to export the subsequent match amount of calculation brought many, the defects such as response is chaotic.
Again, be directly calculate from the lower right corner of dialog boxes carrying out Hough detection computations, according to from right to left, order from top to bottom, the round position detected first exports, and does not need to carry out subsequent calculations, can reduce amount of calculation like this.
Accompanying drawing explanation
Fig. 1 is system function module figure of the present invention.
Fig. 2 is screen capture module flow chart.
Fig. 3 is screen capture module design sketch.
Fig. 4 is QQ acquiescence expression graphical diagram.
Fig. 5 is emoticon locating module process chart.
Fig. 6 is QQ chat window exploded view.
Fig. 7 is the design sketch after gray processing.
Fig. 8 is the design sketch after Gaussian smoothing.
Fig. 9 is emoticon positioning result figure.
Figure 10 is emoticon identification module flow chart.
Figure 11 is that QQ all gives tacit consent to emoticon division figure.
Figure 12 is emoticon recognition result figure.
Embodiment
To develop simultaneously embodiment below in conjunction with accompanying drawing, describe the present invention.
Present invention employs a kind of method without the need to being decrypted analysis to chat content, by chat window monitoring sectional drawing, analyze emoticon, be called sectional drawing Comparison Method.
The method thinking is, first the chat window of immediate communication tool user is monitored, then choose suitable opportunity and carry out sectional drawing and preserve, next the image of chat window is analysed and compared, find out emoticon position, finally identify the implication representated by emoticon.Size due to emoticon is fixing, so can take the scheme of template matches in pattern recognition to realize.
The advantage of this sectional drawing Comparison Method has been to bypass the link cracking encrypting messages, because the method is simple, real-time is good, and can accomplish across immediate communication tool easily.
Fig. 1 is the composition frame chart of the expression recognition apparatus of immediate communication tool of the present invention, and as shown in Figure 1, this expression recognition apparatus comprises chat window monitoring modular, emoticon locating module, emoticon identification module and respond module.Wherein,
Chat window monitoring modular, for after determining that current focus window is the chat window of immediate communication tool, described chat window is monitored, timing or when user has new chat messages to show, the image interception of chat window is got off, and saves as picture; Wherein, focus window refers to the current window operated of user, can judge focus window easily by the api function under Windows.
Emoticon locating module, for analyze chat window monitoring modular intercept the picture got off, find emoticon wherein, after finding emoticon, the position of emoticon sent to described emoticon identification module;
Emoticon identification module, for when behind the position receiving the emoticon that emoticon locating module sends, emoticon in the emoticon of this position and existing emoticon storehouse is contrasted, thus determine the meaning representated by this emoticon, then result is sent to respond module;
Respond module, for after receiving the result that emoticon identification module sends over, is responded by the technique of expression of setting.
Function below for each module is described in detail.
● chat window monitoring modular
The major function of chat window monitoring screen capture module monitors the chat window of user, when user has new chat messages to show, just chat window is intercepted, and save as picture, in order to process and the analysis in later stage, chat window monitoring modular workflow as shown in Figure 2.
For the QQ of company of Tengxun, chat window monitoring modular flow process is roughly like this, first judges that the current focus window of user is QQ chat window when the system is operated, if just enter next step, if not just not responding.After determining that the focus window of user is QQ chat window, need to judge whether that new message enters, if having with regard to sectional drawing and preserve.Or the way of timing sectional drawing can be adopted, every a regular time just to chat window sectional drawing.For whether having can be realized by the change of monitoring chat window epigraph adding of new chat messages, when in chat window during image change, thinking and having new chat messages to enter.The effect of screen capture module as shown in Figure 3.
● emoticon locating module
Obtained the sectional drawing of QQ chat window by chat window monitoring modular, whether following problems faced is exactly how to analyze containing emoticon in the picture that is truncated to, and how to determine the position of emoticon.
First the acquiescence emoticon that QQ carries is analyzed, as shown in Figure 4.For the consideration of practicality and technical reason, native system only considers the classical emoticon of circle supported in QQ acquiescence expression at present.This serial emoticon has two very outstanding features:
1) be circular in shape.
2) be all main color with yellow.
Consider mainly Chinese character, English alphabet, numeral, emoticon that user is used when chatting, first three items is as the distracter in identifying, do not possess the shape facility of the circle of emoticon, but QQ user can the color of self-defined chat text, so also may have this feature yellow.Determine marked by this feature circular and extracted emoticon after considering, this is also the feature of the emoticon that most instant message instrument uses.
Analyze emoticon above and be different from man, English alphabet, the feature of numeral, here just the technology using some image procossing is needed to find circular emoticon, as shown in Figure 5, first the process will cut image, remove the efficiency that unwanted interference region can improve subsequent treatment, that gray processing and image smoothing are carried out to image after cutting, the object of these two flow processs is all strengthen image, to improve the accurate rate detected, be exactly finally detect emoticon, use Hough loop truss function, result is exactly the position i.e. coordinate of circle returning emoticon.
Therefore, this emoticon locating module comprises cutting module, gray processing module, Leveling Block and Hough detection module.
Cutting module, for according to the position of dialog boxes in chat window, cuts out the image of dialog boxes, the image cut out is sent to gray processing module from the image of chat window.
Still for QQ, the sectional drawing of QQ chat window as shown in Figure 6, first the sectional drawing inputted is analyzed, can see that QQ chat window mainly can be divided into four regions, with red line, they are divided out, be respectively function bar, chat record display window, input field, QQ show hurdle, clearly in native system it is desirable that the information of chat record display window, other three regions there will not be emoticon.So cutting this step object is separated from other trizonal encirclement by chat record display window, although I finds that the size of QQ chat window can change according to the needs of user by experiment, the height of function bar: " H
function", the height of input field: " H
input" and QQ show hurdle is wide: " W
elegant", be a fixed value, can not change along with the convergent-divergent of window.Through measuring H
function=105 pixels, H
input=155 pixels, W
elegant=145 pixels.Be easy to just can to extrapolate the origin coordinates of chat record display window according to these three data for (0,105), lower right corner coordinate be (W-145, H-155) wherein W be the wide of whole sectional drawing, H is the height of whole sectional drawing.Be easy to just chat record display window have been shown separately by these data, eliminate very large interference region like this, make follow-up process more efficient.
Gray processing module, for received image is carried out gray processing out, obtains gray-scale map, sends to Leveling Block.
Gray processing is that coloured image is converted to gray level image.The image that screen capture module in the present system obtains is coloured image, coloured image is so a kind of image, its each pixel is to there being three component (R, G, B), these three components represent redness, green, blue, each component can get the integer value in 0 to 255, each class value just represents a color, such pixel can have the value of the color of more than 1,600 ten thousand to select, even be also very huge for this numeral computer, so conveniently process needs to carry out gray processing to image, gray level image is so a kind of image, its pixel is also by R, G, B tri-components represent, but the value of these three components is identical, visible, in gray level image, the span of a pixel only has 255 kinds, and with coloured image the same it still can reflect the colourity of whole and part of entire image and the distribution of brightness degree and feature.So when processing digital picture, generally first converting processed object to gray level image, doing the amount of calculation that can greatly reduce subsequent treatment like this.Gray processing result as shown in Figure 7.
Leveling Block, for carrying out Gaussian smoothing to the gray-scale map received.
The main purpose of image smoothing is the noise in order to eliminate in original image, and keeps edge contour and the lines of original image as far as possible.Noise in image is not restricted to image fault that human eye can aware and distortion, and a lot of noise is only just can be found carrying out Computer Image Processing, and these noises are all random distribution, and size, shape are also all irregular.The method of image smoothing has a variety of, comprises linear, nonlinear smoothing and Edge contrast, Pseudo Col ored Image, filtering etc.When utilizing Gaussian smoothing to remove the disorderly and unsystematic and noise of random distribution, effect more better than other several smoothing method can be received, the most important is that it can obtain reasonable image border, like this follow-up carry out circle detection time can have good accuracy.So carry out Gaussian smoothing to the image of input, the effect after process as shown in Figure 8.
Image after this step of Gaussian smoothing is a gray level image completing denoising, has possessed the precondition of carrying out circle detection.When needing to identify simple geometry pattern in image procossing from image, a kind of basic method is had to be called Hough (Hough) conversion, Hough transform is a kind of basic effective ways realizing rim detection, be in image procossing from original image one of basic skills identifying simple geometric shape.The general principle of Hough transform utilizes point and the duality of line in mathematics, Chosen Point in original image space is transformed to parameter space a curve or curved surface, the point with same parametric characteristics intersects after conversion in parameter space, so just can have been carried out the detection to indicatrix by the accumulation degree and peak value judging point of intersection.Utilize Hough transform the curve detection problem in original image can be converted into the spike problem found in parameter space, namely detection overall permanence is converted into detection local characteristics.Based on the difference of parameter character, Hough transform can detection of straight lines, circle, ellipse, curve etc.
Hough transform a kind ofly has detection method of overall importance, it to random noise and part overlaid phenomenon insensitive, there is extremely strong antijamming capability, can be good at suppressing data point too to concentrate the interference produced.Hough transform has good fault-tolerance and robustness detecting the target side mask of known form, even if having defect or pollute also can by correct identification for target.So present invention employs this method to detect the circle of emoticon.Radius due to emoticon known is about 25 pixels, as long as so navigate to the center of circle and just emoticon can be found and separate, effect as shown in Figure 9.
In order to test validity and the antijamming capability of this method, in sectional drawing, containing the main interference project such as numeral, English alphabet, Chinese character especially, conveniently observe testing result, here testing result exported and identify.Detected two circles in result figure, and these two circles emoticon just, central coordinate of circle with green point identification out, and exports by the circular center of circle, result basic with to expect the same.
After locating module has detected a secondary sectional drawing, have the time of several seconds, wait for the input of new sectional drawing, because this time is very short, so the chat record content in new sectional drawing can have the overlapping of part with former sectional drawing, if contain emoticon in lap, so this emoticon was by what located, if at this time the result detected exported, so will produce repetition.
The reason producing this problem is, the region that QQ shows chat record is fixing, when there being new chat record to arrive, old chat record will be got on by top, if an emoticon has appeared at the bottom of a secondary sectional drawing, namely user has just received this emoticon, so, this emoticon will occur in follow-up several sectional drawings, until there is abundant message that this emoticon is ejected the viewing area of chat record.
Due to above situation, this module can not be arranged to all emoticons detected, all deposit as result exports, in order to solve this problem of resetting, carried out such design: only to coordinate x, y in the emoticon identified, be all that the position of maximum emoticon exports.
Therefore the function of Hough detection module is, carries out Hough transform to the image after Gaussian smoothing, detects the position at circular emoticon place; Only exporting coordinate x, y in the emoticon identified is all the position of maximum emoticon; Wherein x-axis, y-axis with the upper left corner of dialog boxes for zero point.In order to reduce amount of calculation, preferably, the Hough transform of Hough detection module is from the lower right corner of dialog boxes, and according to from right to left, order computation from bottom to up, when first bowlder being detected, exports home position, and stops detecting.
The position of emoticon can be obtained in emoticon locating module, thus emoticon can be separated separately.But only just know that emoticon has appearred in chat window to this step system, it does not also know the meaning representated by this emoticon, so a corresponding response can't be made, realize carrying out correct response to different emoticon, also need to identify the implication representated by isolated emoticon, this process is exactly the function that emoticon identification module can realize.
● emoticon identification module
The main thinking of emoticon identification module is that the emoticon image that obtained by locating module is as template, to the image of all acquiescence emoticons be comprised as global image, then template matches is carried out, finally find out the position of emoticon in global image, owing to containing all emoticons and each emoticon position of having oneself fixing in global image, so just can determine the meaning representated by emoticon according to position, the basic procedure of this module as shown in Figure 10.
Therefore emoticon identification module comprises extraction module, matching module and identification module; Wherein,
Extraction module, for the position exported according to emoticon locating module, obtains emoticon image the image of the described dialog boxes obtained from cutting module, sends to matching module;
Matching module, for using received emoticon image as template, using the image comprising all acquiescence emoticons that prestores as global image, then carry out template matches, finally find out the position of emoticon image in global image;
Identification module, for according to the position range of acquiescence emoticon each in known global image and expression meanings, judges the position of the emoticon image that described matching module is found out which expression meanings corresponding, expression meanings is sent to respond module.
Still all acquiescence emoticon sectional drawing of QQ for QQ, Figure 11.
As can be seen from the figure one 8 row 14 row emoticons are had, amount to 105, each emoticon occupies a fixing position, and there is the boundary rectangle that is fixing, passing through and measuring the area size obtained shared by emoticon rectangle is 33 × 33 pixels, just Figure 11 can be divided into 112 little rectangular areas here, each Regional Representative emoticon, want to identify during emoticon only needs judge templet to mate which region the coordinate of the emoticon returned drops on, such as:
The region of smile emoticon is 0 < x < 33,0 < y < 33.
The curl one's lip region of emoticon is 33 < x < 66,0 < y < 33.
The region of surprised emoticon is 0 < x < 33,33 < y < 66.
The region of sad emoticon is 33 < x < 66,33 < y < 66.
Matching result as shown in figure 12, conveniently observe recognition result, here the image of emoticon to be identified and all images of acquiescence emoticon and the output of recognition result are together illustrated out, and identify the result of template matches with lines, utilize the method successfully can carry out template matches and utilize location recognition to go out the implication of emoticon as seen.
● respond module
The more satisfactory response mode of respond module has accuracy and certain interest, that is this module should be able to be made and the response corresponding to emoticon accurately, user is allowed to be easy to just can understand the implication of response, and require certain interest, can Consumer's Experience be improved like this.
This respond module is find a kind of special peripheral hardware in the plan at paper studies initial stage, and this peripheral hardware should have following characteristic:
1) face can be imitated and make the various expressions such as happiness, anger, grief and joy.
2) can be connected on the main frame of user by some way, communicate with subscriber's main station.
3) this peripheral hardware can be controlled by programming and make different expressions.
Transmission means can be selected according to actual needs, the content of the data of transmission should do following design, 105 emoticons are numbered at identification module, the result identified is exactly the numbering of emoticon, so the state of expression recognition apparatus also can be numbered, this numbering should be consistent with the numbering of emoticon.Numbering is so only needed to send to respond module, just can make corresponding expression to have responded, so the data content transmitted can be designed to the integer between 1 to 105, when respond module receives numbering, just can change to corresponding state, so this state is exactly just in time state corresponding to emoticon.
In sum, these are only preferred embodiment of the present invention, be not intended to limit protection scope of the present invention.Within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (2)
1. based on an expression recognition apparatus for immediate communication tool, it is characterized in that, comprise chat window monitoring modular, emoticon locating module, emoticon identification module and respond module;
Described chat window monitoring modular, for after determining that current focus window is the chat window of immediate communication tool, described chat window is monitored, timing or when user has new chat messages to show, the image interception of chat window is got off, and saves as picture;
Described emoticon locating module, for analyze chat window monitoring modular intercept the picture got off, find emoticon wherein, after finding emoticon, the position of emoticon sent to described emoticon identification module;
Described emoticon identification module, for when behind the position receiving the emoticon that emoticon locating module sends, emoticon in the emoticon of this position and known emoticon storehouse is contrasted, thus determine the meaning representated by this emoticon, then result is sent to respond module;
Described respond module, for after receiving the result that emoticon identification module sends over, is responded by the technique of expression of setting;
Further, described emoticon locating module comprises cutting module, gray processing module, Leveling Block and Hough Hough detection module:
Cutting module, for according to the position of dialog boxes in chat window, cuts out the image of dialog boxes, the image cut out is sent to gray processing module from the image of chat window;
Gray processing module, for received image is carried out gray processing out, obtains gray-scale map, sends to Leveling Block;
Leveling Block, for carrying out Gaussian smoothing to the gray-scale map received;
Hough detection module, for carrying out Hough transform to the image after Gaussian smoothing, detects the position at circular emoticon place; Only exporting coordinate x, y in the emoticon identified is all the position of maximum emoticon; Wherein x-axis, y-axis with the upper left corner of dialog boxes for zero point;
Wherein, the Hough transform of described Hough detection module is from the lower right corner of dialog boxes, and according to from right to left, order computation from bottom to up, when first bowlder being detected, exports home position, and stops detecting;
Further, described emoticon identification module comprises extraction module, matching module and identification module;
Described extraction module, for the position exported according to emoticon locating module, obtains emoticon image the image of the described dialog boxes obtained from cutting module, sends to matching module;
Described matching module, for using received emoticon image as template, using the image comprising all acquiescence emoticons that prestores as global image, then carry out template matches, finally find out the position of emoticon image in global image;
Identification module in described emoticon identification module, for according to the position range of acquiescence emoticon each in known global image and expression meanings, judge the position of the emoticon image that described matching module is found out which expression meanings corresponding, expression meanings is sent to respond module.
2. expression recognition apparatus as claimed in claim 1, it is characterized in that, described respond module is responded by sound, image and/or action.
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| CN105204748B (en) * | 2014-06-27 | 2019-09-17 | 阿里巴巴集团控股有限公司 | Terminal interaction method and its device |
| CN104699662B (en) * | 2015-03-18 | 2017-12-22 | 北京交通大学 | The method and apparatus for identifying overall symbol string |
| CN106445478B (en) * | 2015-08-12 | 2020-06-05 | 腾讯科技（深圳）有限公司 | Method and device for converting graphic expressions |
| CN106228156B (en) * | 2016-07-18 | 2019-09-20 | 百度在线网络技术（北京）有限公司 | A kind of method and apparatus of determining information alert content |
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