CN102750555A - Expression robot applied to instant messaging tool - Google Patents

Expression robot applied to instant messaging tool Download PDF

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CN102750555A
CN102750555A CN2012102244961A CN201210224496A CN102750555A CN 102750555 A CN102750555 A CN 102750555A CN 2012102244961 A CN2012102244961 A CN 2012102244961A CN 201210224496 A CN201210224496 A CN 201210224496A CN 102750555 A CN102750555 A CN 102750555A
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emoticon
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emoticons
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CN102750555B (en
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张纯纯
王崇文
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Beijing Institute of Technology BIT
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Abstract

本发明公开了一种应用于即时通讯工具的表情机器人,它可以实时地识别用户所使用的表情符号,并且做出与该表情符号所代表含义一样的响应。而且表情识别方法避免了复杂程度高、实时性不佳、即时通讯工具升级后需要重新破译密钥的缺陷。该系统中,聊天窗口监测模块在即时通讯工具有新的聊天消息显示出来时或定时将聊天窗口的图像截取为图片保存;表情符号定位模块在截取下来的图片中寻找表情符号,将表情符号的位置发送给表情符号识别模块;表情符号识别模块将表情符号的位置与已知表情符号库中的表情符号进行对比,确定表情符号的意义,并发送给响应模块;响应模块在接收到表情符号识别模块发送过来的结果后,通过设定的表现方法进行响应。

Figure 201210224496

The invention discloses an emoticon robot applied to an instant messaging tool, which can recognize emoticons used by users in real time, and respond with the same meaning as the emoticons represent. Moreover, the expression recognition method avoids the defects of high complexity, poor real-time performance, and the need to re-decipher the key after the upgrade of the instant messaging tool. In this system, the chat window monitoring module intercepts the image of the chat window as a picture when the instant messaging tool has a new chat message to display or regularly saves it as a picture; The position is sent to the emoticon recognition module; the emoticon recognition module compares the position of the emoticon with the emoticons in the known emoticon library, determines the meaning of the emoticon, and sends it to the response module; the response module receives the emoji recognition After the result sent by the module, it responds with the set expression method.

Figure 201210224496

Description

一种应用于即时通讯工具的表情机器人An expression robot applied to instant messaging tools

技术领域 technical field

本发明是一种基于即时通讯工具的表情机器人,具体涉及屏幕捕捉、图像识别技术领域。The invention is an expression robot based on an instant messaging tool, and specifically relates to the technical fields of screen capture and image recognition.

背景技术 Background technique

即时通讯工具又称为即时聊天工具,是一种基于互联网的服务,经过十几年的发展,如今已经拥有大量的固定用户,渗透到我们生活和工作中的方方面面。表情符号诞生在互联网,原本只是一种网络次文化,但随着网络的迅速发展与普及,它得到了人们的广泛接受。Instant messaging tool, also known as instant messaging tool, is an Internet-based service. After more than ten years of development, it now has a large number of regular users and penetrates into every aspect of our life and work. Emoji was born on the Internet. It was originally just an Internet subculture, but with the rapid development and popularization of the Internet, it has been widely accepted by people.

一般的即时通讯工具都拥有插入表情符号的功能,极大方便了用户的表达,增强了交流乐趣和用户体验。目前,表情符号主要朝着更加多元,更加生动和复杂的方向发展,本发明提出了一条创造性的发展道路:让表情符号更加真实化。该方案能够对即时通讯工具的窗口界面进行监测,然后识别用户使用的表情符号的含义,并且针对被识别的表情符号做出符合该表情符号含义的响应。通过表情机器人用户可以更加直观地感受到聊天过程中所使用的表情符号,由此来增加即时通讯用户的体验感和乐趣。这是一个创新性的产品,鲜有对前人经验的借鉴。General instant messaging tools have the function of inserting emoticons, which greatly facilitates the expression of users and enhances the fun of communication and user experience. At present, emoticons are mainly developing in a more diverse, vivid and complex direction. The present invention proposes a creative development path: making emoticons more realistic. The solution can monitor the window interface of the instant messaging tool, and then recognize the meaning of the emoticon used by the user, and respond to the recognized emoticon according to the meaning of the emoticon. Through the emoticon robot, the user can more intuitively feel the emoticons used in the chat process, thereby increasing the experience and fun of the instant messaging user. This is an innovative product with little reference to previous experience.

在进行表情符号识别方案的设计时,首先想到的是对即时通讯工具传输的数据包进行解密分析,从中提取出表情符号的代码,从而实现识别。但是目前的即时通讯工具都会在聊天内容的传送过程中对其进行很复杂加密,破译密钥需要比较长的时间,难度较大,而且即时通讯工具通常会不定期的升级,每次升级都会重新设定密钥,因此即时通讯工具升级后需要重新破译密钥的缺陷,这就带来了该方案的需要不断破译密钥的缺陷、复杂程度高、实时性不佳,从而无法批量的生产和推广。When designing the emoticon recognition scheme, the first thing that comes to mind is to decrypt and analyze the data packets transmitted by the instant messaging tool, and extract the code of the emoticon from it, so as to realize the recognition. However, the current instant messaging tools will perform complex encryption on the chat content during the transmission process, and it will take a long time to decipher the key, which is difficult, and the instant messaging tools are usually upgraded from time to time, and each upgrade will be restarted. Set the key, so the defect that the instant messaging tool needs to decipher the key again after the upgrade, which brings about the defect that the program needs to continuously decipher the key, the complexity is high, and the real-time performance is not good, so it cannot be mass-produced and promote.

发明内容 Contents of the invention

有鉴于此,本发明提供了一种应用于即时通讯工具的表情机器人,它可以实时地识别用户所使用的表情符号,并且做出与该表情符号所代表含义一样的响应。而且,其表情识别方法并非采用对即时通讯工具传输的数据包进行解密分析的方法,避免了采用这种方案所带来的复杂程度高、实时性不佳、即时通讯工具升级后需要重新破译密钥的缺陷。In view of this, the present invention provides an emoticon robot applied to instant messaging tools, which can recognize emoticons used by users in real time, and respond with the same meaning as the emoticons represent. Moreover, its expression recognition method does not use the method of decrypting and analyzing the data packets transmitted by the instant messaging tool, which avoids the high complexity, poor real-time performance, and the need to re-decipher the password after the instant messaging tool is upgraded. key defect.

该方法是这样实现的:The method is implemented like this:

一种基于即时通讯工具的表情机器人,包括聊天窗口监测模块、表情符号定位模块、表情符号识别模块和响应模块;An emoticon robot based on an instant messaging tool, including a chat window monitoring module, an emoticon positioning module, an emoticon recognition module and a response module;

所述聊天窗口监测模块,用于在确定当前焦点窗口是即时通讯工具的聊天窗口后,对所述聊天窗口进行监测,定时或当用户有新的聊天消息显示出来时,将聊天窗口的图像截取下来,并保存为图片;The chat window monitoring module is used to monitor the chat window after determining that the current focus window is the chat window of the instant messaging tool, and intercept the image of the chat window regularly or when a new chat message is displayed by the user down, and save as a picture;

所述表情符号定位模块,用于分析聊天窗口监测模块所截取下来的图片,寻找其中的表情符号,找到表情符号之后,将表情符号的位置发送给所述表情符号识别模块;The emoticon positioning module is used to analyze the pictures intercepted by the chat window monitoring module, find the emoticons therein, and after finding the emoticons, send the position of the emoticons to the emoticon recognition module;

所述表情符号识别模块,用于当接收到表情符号定位模块发过来的表情符号的位置后,将该位置的表情符号与现有表情符号库中的表情符号进行对比,从而确定该表情符号所代表的意义,然后将结果发送给响应模块;The emoticon recognition module is used to compare the emoticon at the position with the emoticon in the existing emoticon library after receiving the emoticon position sent by the emoticon positioning module, so as to determine the emoticon in the emoticon. The meaning of the representative, and then send the result to the response module;

所述响应模块,用于在接收到表情符号识别模块发送过来的结果后,通过设定的表现方法进行响应。The response module is used for responding through the set expression method after receiving the result sent by the emoticon recognition module.

其中,所述响应模块通过声音、图像和/或动作进行响应。Wherein, the response module responds through sound, image and/or action.

优选地,所述表情符号定位模块包括切割模块、灰度化模块、平滑模块和哈夫Hough检测模块:Preferably, the emoticon positioning module includes a cutting module, a graying module, a smoothing module and a Hough Hough detection module:

切割模块,用于根据对话栏在聊天窗口中的位置,从聊天窗口的图像中将对话栏的图像切割出来,将切割出来的图像发送给灰度化模块;The cutting module is used to cut out the image of the dialogue bar from the image of the chat window according to the position of the dialogue bar in the chat window, and send the cut image to the grayscale module;

灰度化模块,用于将所接收的图像进行灰度化出来,得到灰度图,发送给平滑模块;The grayscale module is used to grayscale the received image to obtain a grayscale image and send it to the smoothing module;

平滑模块,用于对接收到的灰度图进行高斯平滑处理;A smoothing module is used to perform Gaussian smoothing on the received grayscale image;

Hough检测模块,用于对高斯平滑处理后的图像进行Hough变换,检测出圆形的表情符号所在的位置;只输出识别出的表情符号中坐标x、y都是最大的表情符号的位置;其中x轴、y轴以对话栏的左上角为零点。优选地,所述Hough检测模块的Hough变换从对话栏的右下角开始,按照从右至左,从下至上的顺序计算,当检测到第一个圆时,输出圆心位置,并停止检测。The Hough detection module is used to carry out Hough transform to the image after Gaussian smoothing, and detects the position of the circular emoticon; only outputs the position where coordinates x and y are the largest emoticon in the emoticon recognized; The x-axis and y-axis take the upper left corner of the dialogue bar as the zero point. Preferably, the Hough transform of the Hough detection module starts from the lower right corner of the dialogue column, and is calculated in the order from right to left and from bottom to top. When the first circle is detected, the position of the center of the circle is output, and the detection is stopped.

优选地,所述表情符号识别模块包括提取模块、匹配模块和识别模块;Preferably, the emoticon recognition module includes an extraction module, a matching module and a recognition module;

所述提取模块,用于根据表情符号定位模块输出的位置,从切割模块获得的所述对话栏的图像中获得表情符号图像,发送给匹配模块;The extraction module is used to obtain the emoticon image from the image of the dialogue column obtained by the cutting module according to the position output by the emoticon positioning module, and send it to the matching module;

所述匹配模块,用于将所接收的表情符号图像作为模板,将预先存储的包含所有默认表情符号的图像作为全局图像,然后进行模板匹配,最后找出表情符号图像在全局图像中的位置;The matching module is used to use the received emoticon image as a template, and pre-stored images containing all default emoticons as a global image, then perform template matching, and finally find out the position of the emoticon image in the global image;

所述识别模块,用于根据已知的全局图像中每个默认表情符号的位置范围和表情含义,判断所述匹配模块找出的表情符号图像的位置对应哪个表情含义,将表情含义发送给响应模块。The recognition module is used to judge which expression meaning corresponds to the position of the emoticon image found by the matching module according to the position range and expression meaning of each default emoticon in the known global image, and send the expression meaning to the response module.

有益效果:Beneficial effect:

本发明提供了一种应用于即时通讯工具的表情机器人,可以实时地识别用户所使用的表情符号,并且做出与该表情符号所代表含义一样的响应,而且更重要的是,该表情及其人的表情识别方法并非采用对即时通讯工具传输的数据包进行解密分析的方法,即时通讯工具升级后不需要重新破译密钥,因此通用性好,适用于各种即时通讯工具。而且该方法依靠截图进行表情识别,方法简单,可以借助很多现有的图像处理方法,实现起来十分简单,而且计算量也不大,从而有利于提高表情识别的实时性。The invention provides an emoticon robot applied to an instant messaging tool, which can recognize the emoticon used by the user in real time, and make a response that is the same as the meaning represented by the emoticon, and more importantly, the emoticon and its The facial expression recognition method does not adopt the method of decrypting and analyzing the data packets transmitted by the instant messaging tool. After the instant messaging tool is upgraded, it does not need to decipher the key again, so it has good versatility and is suitable for various instant messaging tools. Moreover, this method relies on screenshots for facial expression recognition, which is simple and can be implemented with the help of many existing image processing methods, and the calculation amount is not large, which is conducive to improving the real-time performance of facial expression recognition.

其次,在Hough圆检测后可能会得到多个位于不同位置的圆,这里根据即时通讯工具的特点只输出x、y最大的圆的位置,从而避免了多个圆位置输出带来的后续匹配计算量多,响应混乱等缺陷。Secondly, after Hough circle detection, multiple circles at different positions may be obtained. According to the characteristics of the instant messaging tool, only the position of the circle with the largest x and y is output, thus avoiding subsequent matching calculations caused by the output of multiple circle positions Large amount, response confusion and other defects.

再次,在进行Hough检测计算是,直接从对话栏的右下角开始计算,按照从右到左,从下到上的顺序,将第一个检测到的圆位置输出,且不需要进行后续计算,这样可以减少计算量。Again, when performing Hough detection calculations, start calculations directly from the lower right corner of the dialog box, and output the first detected circle position in the order from right to left, bottom to top, and do not need to perform subsequent calculations. This reduces computation.

附图说明 Description of drawings

图1为本发明的系统功能模块图。Fig. 1 is a system functional block diagram of the present invention.

图2为截图模块流程图。Figure 2 is a flowchart of the screenshot module.

图3为截图模块效果图。Figure 3 is the effect diagram of the screenshot module.

图4为QQ默认表情符号图。Figure 4 is a QQ default emoticon map.

图5为表情符号定位模块处理流程图。Fig. 5 is a flow chart of emoticon location module processing.

图6为QQ聊天窗口分解图。Figure 6 is an exploded view of the QQ chat window.

图7为灰度化后的效果图。Figure 7 is an effect diagram after grayscale.

图8为高斯平滑之后的效果图。Figure 8 is the effect diagram after Gaussian smoothing.

图9为表情符号定位结果图。Fig. 9 is a diagram of emoticon positioning results.

图10为表情符号识别模块流程图。Figure 10 is a flow chart of the emoticon recognition module.

图11为QQ全部默认表情符号划分图。Figure 11 is a division diagram of all default emoticons in QQ.

图12为表情符号识别结果图。Fig. 12 is a graph of emoticon recognition results.

具体实施方式 Detailed ways

下面结合附图并举实施例,对本发明进行详细描述。The present invention will be described in detail below with reference to the accompanying drawings and examples.

本发明采用了一种无需对聊天内容进行解密分析的方法,通过对聊天窗口监测截图,分析出表情符号,称为截图比对法。The present invention adopts a method that does not need to decrypt and analyze the chat content, and analyzes the emoticons by monitoring the screenshots of the chat window, which is called the comparison method of screenshots.

该方法思路是,首先对即时通讯工具用户的聊天窗口进行监测,然后选取合适的时机进行截图并保存,接下来对聊天窗口的图像进行分析比对,找出表情符号位置,最后识别出表情符号所代表的含义。由于表情符号的大小是固定的,所以可以采取模式识别中模板匹配的方案来实现。The idea of this method is to first monitor the chat window of the user of the instant messaging tool, then select an appropriate time to take a screenshot and save it, then analyze and compare the images of the chat window to find out the position of the emoticon, and finally recognize the emoticon the meaning represented. Since the size of the emoticon is fixed, it can be realized by adopting the scheme of template matching in pattern recognition.

该截图比对法的优势是绕过了破解加密消息的环节,因此方法简单、实时性好,并且可以很容易的做到跨即时通讯工具。The screenshot comparison method has the advantage of bypassing the link of deciphering encrypted messages, so the method is simple, has good real-time performance, and can be easily implemented across instant messaging tools.

图1为本发明即时通讯工具的表情机器人的组成框图,如图1所示,该表情机器人包括聊天窗口监测模块、表情符号定位模块、表情符号识别模块和响应模块。其中,Fig. 1 is a composition block diagram of an emoticon robot of an instant messaging tool of the present invention. As shown in Fig. 1, the emoticon robot includes a chat window monitoring module, an emoticon positioning module, an emoticon recognition module and a response module. in,

聊天窗口监测模块,用于在确定当前焦点窗口是即时通讯工具的聊天窗口后,对所述聊天窗口进行监测,定时或当用户有新的聊天消息显示出来时,将聊天窗口的图像截取下来,并保存为图片;其中,焦点窗口是指用户当前正在操作的窗口,通过Windows下的API函数可以很容易的判断出焦点窗口。The chat window monitoring module is used to monitor the chat window after determining that the current focus window is the chat window of the instant messaging tool, and to intercept the image of the chat window at regular intervals or when a new chat message is displayed by the user, And save it as a picture; wherein, the focus window refers to the window that the user is currently operating, and the focus window can be easily judged through the API function under Windows.

表情符号定位模块,用于分析聊天窗口监测模块所截取下来的图片,寻找其中的表情符号,找到表情符号之后,将表情符号的位置发送给所述表情符号识别模块;The emoticon positioning module is used to analyze the pictures intercepted by the chat window monitoring module, find emoticons therein, and after finding emoticons, send the position of emoticons to the emoticon recognition module;

表情符号识别模块,用于当接收到表情符号定位模块发过来的表情符号的位置后,将该位置的表情符号与现有表情符号库中的表情符号进行对比,从而确定该表情符号所代表的意义,然后将结果发送给响应模块;The emoticon recognition module is used to compare the emoticon at the position with the emoticon in the existing emoticon library after receiving the position of the emoticon sent by the emoticon positioning module, so as to determine the emoticon represented by the emoticon meaning, and then send the result to the response module;

响应模块,用于在接收到表情符号识别模块发送过来的结果后,通过设定的表现方法进行响应。The response module is used for responding through the set expression method after receiving the result sent by the emoticon recognition module.

下面针对每个模块的功能进行详细描述。The function of each module is described in detail below.

●聊天窗口监测模块●Chat window monitoring module

聊天窗口监测截图模块的主要功能是对用户的聊天窗口进行监视,当用户有新的聊天消息显示出来时,就将聊天窗口截取下来,并保存为图片,以备后期的处理和分析,聊天窗口监测模块工作流程如图2所示。The main function of the chat window monitoring screenshot module is to monitor the user's chat window. When the user has a new chat message displayed, the chat window will be intercepted and saved as a picture for later processing and analysis. Chat window The workflow of the monitoring module is shown in Figure 2.

以腾讯公司的QQ为例,聊天窗口监测模块大致的流程是这样,当系统运行时首先判断用户当前的焦点窗口是不是QQ聊天窗口,如果是就进入下一步,如果不是就不做响应。当已经确定用户的焦点窗口是QQ聊天窗口后,需要判断是否有新的消息进入,如果有就截图并保存下来。或者可以采用定时截图的办法,每隔一个固定的时间就对聊天窗口截图。对于是否有新聊天消息的加入可以通过监控聊天窗口上图像的变化实现,当聊天窗口内图像变化时,认为有新的聊天消息进入。截图模块的效果如图3所示。Taking Tencent's QQ as an example, the general process of the chat window monitoring module is as follows. When the system is running, it first judges whether the user's current focus window is a QQ chat window. If it is, it will enter the next step. If not, it will not respond. After it has been determined that the user's focus window is the QQ chat window, it is necessary to judge whether there is a new message entering, and if so, take a screenshot and save it. Or you can use the method of timing screenshots, and take screenshots of the chat window every fixed time. Whether new chat messages are added can be realized by monitoring the change of the image on the chat window. When the image in the chat window changes, it is considered that a new chat message has entered. The effect of the screenshot module is shown in Figure 3.

●表情符号定位模块●Emoji positioning module

通过聊天窗口监测模块得到了QQ聊天窗口的截图,接下来面临的问题就是怎么样分析截取到的图片中是否含有表情符号,以及如何确定表情符号的位置。The screenshot of the QQ chat window is obtained through the chat window monitoring module. The next problem is how to analyze whether the captured picture contains emoticons, and how to determine the location of the emoticons.

首先分析QQ自带的默认表情符号,如图4所示。出于实用性和技术原因的考虑,本系统目前只考虑支持QQ默认表情中的圆形经典表情符号。这一系列表情符号有两个很突出的特征:First, analyze the default emoticons that come with QQ, as shown in Figure 4. For practical and technical reasons, this system currently only considers supporting the circular classic emoticons in QQ default emoticons. This series of emoji has two very prominent features:

1)形状上是圆形。1) It is circular in shape.

2)都以黄色为主要颜色。2) Both use yellow as the main color.

考虑到用户在聊天时所用的主要是汉字、英文字母、数字、表情符号,前三项作为识别过程中的干扰项,不具备表情符号的圆形的形状特征,但是QQ用户可以自定义聊天文本的颜色,所以也可能具有黄色这个特征。在综合考虑之后决定通过圆形这个特征来标记并提取表情符号,这也是大多及时通讯工具所使用的表情符号的特征。Considering that users mainly use Chinese characters, English letters, numbers, and emoticons when chatting, the first three items are interference items in the recognition process and do not have the circular shape of emoticons, but QQ users can customize chat text color, so it may also have the characteristic of yellow. After comprehensive consideration, it was decided to use the feature of circle to mark and extract emoji, which is also the feature of emoji used by most instant messaging tools.

前面分析了表情符号不同于汉子、英文字母、数字的特征,这里就需要用到一些图像处理的技术来寻找圆形的表情符号,如图5所示,首先要对图像进行切割的处理,除去不需要的干扰区域可以提高后续处理的效率,切割之后是对图像进行灰度化和图像平滑,这两个流程的目的都是增强图像,以便提高检测的精确率,最后就是检测表情符号,用到了Hough圆检测函数,结果就是返回表情符号的位置即圆形的坐标。Previously analyzed the characteristics of emoticons that are different from Chinese characters, English letters, and numbers, here we need to use some image processing techniques to find circular emoticons, as shown in Figure 5, first of all, we need to cut the image, remove Unnecessary interference areas can improve the efficiency of subsequent processing. After cutting, the image is grayscaled and image smoothed. The purpose of these two processes is to enhance the image in order to improve the accuracy of detection. Finally, it is to detect emoticons. Use When it comes to the Hough circle detection function, the result is to return the position of the emoji, that is, the coordinates of the circle.

因此,该表情符号定位模块包括切割模块、灰度化模块、平滑模块和Hough检测模块。Therefore, the emoticon localization module includes a cutting module, a graying module, a smoothing module and a Hough detection module.

切割模块,用于根据对话栏在聊天窗口中的位置,从聊天窗口的图像中将对话栏的图像切割出来,将切割出来的图像发送给灰度化模块。The cutting module is configured to cut the image of the dialogue bar from the image of the chat window according to the position of the dialogue bar in the chat window, and send the cut image to the grayscale module.

仍以QQ为例,QQ聊天窗口的截图如图6所示,首先来分析一下输入的截图,可以看到QQ聊天窗口主要可以分为四个区域,用红线将他们划分出来,分别为功能栏、聊天记录显示窗口、输入栏、QQ秀栏,很明显在本系统里需要的是聊天记录显示窗口的信息,其它三个区域不会出现表情符号。所以,切割这一步目的是将聊天记录显示窗口从其它三个区域的包围中分离出来,通过实验我发现虽然QQ聊天窗口的大小是可以根据用户的需要而改变的,但是功能栏的高:“H功能”,输入栏的高:“H输入”以及QQ秀栏的宽:“W”,是一个固定值,不会随着窗口的缩放而改变。经过测量H功能=105像素,H输入=155像素,W=145像素。根据这三个数据很容易就可以推算出聊天记录显示窗口的起始坐标为(0,105),右下角坐标为(W-145,H-155)其中W为整个截图的宽,H为整个截图的高。通过这些数据很容易就可以将聊天记录显示窗口单独显示出来了,这样做剔除了很大的干扰区域,使得后续的处理更加高效。Still taking QQ as an example, the screenshot of the QQ chat window is shown in Figure 6. First, let’s analyze the input screenshot. You can see that the QQ chat window can be divided into four areas, which are divided by red lines, which are function bars , chat record display window, input column, QQ show column, obviously what is needed in this system is the information of the chat record display window, and emoticons will not appear in the other three areas. Therefore, the purpose of cutting this step is to separate the chat record display window from the encirclement of the other three areas. Through experiments, I found that although the size of the QQ chat window can be changed according to the user's needs, the height of the function bar: " H function ", the height of the input column: "H input " and the width of the QQ show column: "W show ", are a fixed value and will not change with the zoom of the window. After measuring H function = 105 pixels, H input = 155 pixels, W show = 145 pixels. According to these three data, it is easy to deduce that the starting coordinates of the chat record display window are (0, 105), and the coordinates of the lower right corner are (W-145, H-155), where W is the width of the entire screenshot, and H is the entire The height of the screenshot. Through these data, it is easy to display the chat record display window separately, which eliminates a large interference area and makes subsequent processing more efficient.

灰度化模块,用于将所接收的图像进行灰度化出来,得到灰度图,发送给平滑模块。The grayscale module is used to grayscale the received image to obtain a grayscale image and send it to the smoothing module.

灰度化是将彩色图像转换为灰度图像。在本系统中的截图模块所获取的图像是彩色图像,彩色图像是这样一种图像,它的每个像素点都对应有三个分量(R,G,B),这三个分量代表红色、绿色、蓝色,每个分量可以取0到255中的整数值,每一组值就代表了一个颜色,这样一个像素点可以有1600多万的颜色的取值选择,即使是对于计算机来说这个数字也是十分庞大的,所以为了方便处理需要对图像进行灰度化,灰度图像是这样一种图像,它的像素点也由R、G、B三个分量来表示,但是这三个分量的取值相同,可见,在灰度图像中一个像素点的取值范围只有255种,并且跟彩色图像一样它仍然可以反映整幅图像的整体和局部的色度和亮度等级的分布和特征。所以在对数字图像进行处理时,一般先将被处理对象转换成灰度图像,这样做可以大大减少后续处理的计算量。灰度化结果如图7所示。Grayscaling is the conversion of a color image into a grayscale image. The image acquired by the screenshot module in this system is a color image. A color image is such an image that each pixel corresponds to three components (R, G, B), and these three components represent red and green. , blue, each component can take an integer value from 0 to 255, each group of values represents a color, such a pixel can have more than 16 million color values to choose from, even for a computer The numbers are also very large, so for the convenience of processing, it is necessary to grayscale the image. A grayscale image is such an image, and its pixels are also represented by three components of R, G, and B, but the three components of these three components The value is the same, it can be seen that the value range of a pixel in the grayscale image is only 255, and it can still reflect the distribution and characteristics of the overall and local chromaticity and brightness levels of the entire image just like the color image. Therefore, when processing digital images, the object to be processed is generally converted into a grayscale image first, which can greatly reduce the amount of calculation for subsequent processing. The grayscale result is shown in Figure 7.

平滑模块,用于对接收到的灰度图进行高斯平滑处理。The smoothing module is used to perform Gaussian smoothing on the received grayscale image.

图像平滑的主要目的是为了消除原图像中的噪声,并且尽量保持原图像的边缘轮廓和线条。图像中的噪声并不仅仅限于人类眼睛所能觉察到的图像失真和变形,很多噪声只有在进行计算机图像处理是才能被发现,并且这些噪声都是随机分布,大小、形状也都是不规则的。图像平滑的方法有很多种,包括线性、非线性平滑和锐化处理,伪彩色处理,滤波等。利用高斯平滑去除杂乱无章并且随机分布的噪声时,会收到比其它几种平滑方法更好的效果,最重要的一点是它可以得到比较好的图像边缘,这样在后续进行圆形检测时可以有不错的精确度。所以对输入的图像进行高斯平滑处理,处理后的效果如图8所示。The main purpose of image smoothing is to eliminate the noise in the original image and keep the edge contours and lines of the original image as much as possible. The noise in the image is not limited to the image distortion and deformation that can be perceived by human eyes. Many noises can only be found in computer image processing, and these noises are randomly distributed, and the size and shape are also irregular. . There are many methods of image smoothing, including linear and nonlinear smoothing and sharpening, false color processing, filtering, etc. When Gaussian smoothing is used to remove chaotic and randomly distributed noise, it will receive better results than other smoothing methods. The most important point is that it can get better image edges, so that it can be used in subsequent circle detection. Nice precision. Therefore, Gaussian smoothing is performed on the input image, and the effect after processing is shown in Figure 8.

经过高斯平滑处理这一步之后的图像,是一个完成去噪的灰度图像,已经具备了进行圆形检测的前置条件。当在图像处理中需要从图像中识别简单几何图案时,有一种基本的方法叫做哈夫(Hough)变换,Hough变换是实现边缘检测的一种基本的有效方法,是图像处理中从原图像中识别出简单几何形状的基本方法之一。Hough变换的基本原理是利用点与线在数学中的对偶性,将原始图像空间中的选定点变换到参数空间的的一条曲线或曲面,具有同一参量特征的点经过变换后在参量空间中相交,这样就可以通过判断交点处的积累程度即峰值来完成对特征曲线的检测。利用Hough变换可以把原始图像中的曲线检测问题转化为寻找参数空间中的峰值问题,也就是把检测整体特性转化为检测局部特性。基于参量性质的不同,Hough变换可以检测直线、圆、椭圆、曲线等。The image after Gaussian smoothing is a denoised grayscale image, which already has the prerequisites for circle detection. When it is necessary to recognize simple geometric patterns from images in image processing, there is a basic method called Hough transform. Hough transform is a basic and effective method for edge detection. One of the basic methods for identifying simple geometric shapes. The basic principle of Hough transform is to use the duality of point and line in mathematics to transform the selected point in the original image space into a curve or surface in the parameter space, and the points with the same parameter characteristics are transformed in the parameter space Intersect, so that the detection of the characteristic curve can be completed by judging the degree of accumulation at the intersection point, that is, the peak value. Using the Hough transform, the problem of curve detection in the original image can be transformed into the problem of finding the peak in the parameter space, that is, the detection of the overall characteristics can be transformed into the detection of local characteristics. Based on the different properties of the parameters, the Hough transform can detect straight lines, circles, ellipses, curves, etc.

Hough变换是一种具有全局性的检测方法,它对随机噪声和部分遮盖现象不敏感,具有极强的抗干扰能力,能够很好的抑制数据点过于集中所产生的干扰。Hough变换在检测已知形状的目标方面具有良好的容错性和鲁棒性,即使目标有缺损或污染也能够被正确的识别。所以本发明采用了这种方法来检测表情符号的圆形。由于表情符号的半径是已知的约为25个像素点,所以只要定位到圆心就可以将表情符号找到并分离出来,效果如图9所示。Hough transform is a global detection method, it is insensitive to random noise and partial cover phenomenon, has strong anti-interference ability, and can well suppress the interference caused by too concentrated data points. Hough transform has good fault tolerance and robustness in detecting objects with known shapes, even if the objects are damaged or polluted, they can be correctly identified. So the present invention adopts this method to detect the circle of the emoticon. Since the radius of the emoticon is known to be about 25 pixels, the emoticon can be found and separated as long as the center of the circle is located, and the effect is shown in Figure 9 .

为了测试本方法的有效性和抗干扰能力,特别在截图里包含了数字、英文字母、汉字等主要的干扰项目,为了方便观察检测结果,这里将检测结果进行了输出和标识。结果图中检测出了两个圆形,并且这两个圆形正是表情符号,圆形的圆心用绿色点标识了出来,并且将圆心坐标进行了输出,结果基本与预期的一样。In order to test the effectiveness and anti-interference ability of this method, the main interference items such as numbers, English letters, and Chinese characters are included in the screenshots. In order to facilitate the observation of the test results, the test results are output and marked here. Two circles are detected in the result image, and these two circles are exactly emojis. The center of the circle is marked with a green dot, and the coordinates of the center are output. The result is basically the same as expected.

当定位模块检测完一副截图之后,会有几秒的时间,来等待新截图的输入,由于这个时间很短,所以,新截图中的聊天记录内容会与以前的截图有部分的重叠,如果重叠部分中包含了表情符号,那么这个表情符号已经是被定位过的了,如果这时候将检测到的结果输出,那么就会产生重复。After the positioning module detects a screenshot, there will be a few seconds to wait for the input of the new screenshot. Since this time is very short, the content of the chat history in the new screenshot will partially overlap with the previous screenshot. If If an emoji is contained in the overlapping part, then the emoji has already been located. If the detected result is output at this time, duplication will occur.

产生这个问题的原因是,QQ显示聊天记录的区域是固定的,当有新的聊天记录到来时,旧的聊天记录就会被顶上去,如果一个表情符号出现在了一副截图的最底层,即用户刚收到这个表情符号,那么,这个表情符号就会在后续的几张截图里出现,直到有足够多的消息将此表情符号顶出聊天记录的显示区域。The reason for this problem is that the area where QQ displays chat records is fixed. When new chat records arrive, the old chat records will be topped up. If an emoji appears at the bottom of a screenshot, That is, the user has just received the emoticon, then the emoticon will appear in several subsequent screenshots until there are enough messages to push the emoticon out of the display area of the chat history.

由于以上的情况,本模块不能设置成将所有检测到的表情符号,全部存放为结果进行输出,为了解决重复定位这个问题,进行了这样的设计:只对识别出的表情符号中坐标x、y、都是最大的表情符号的位置进行输出。Due to the above situation, this module cannot be set to store all the detected emoticons as results for output. In order to solve the problem of repeated positioning, this design is carried out: only the coordinates x and y of the recognized emoticons , are the positions of the largest emoticons for output.

因此Hough检测模块的功能是,对高斯平滑处理后的图像进行Hough变换,检测出圆形的表情符号所在的位置;只输出识别出的表情符号中坐标x、y都是最大的表情符号的位置;其中x轴、y轴以对话栏的左上角为零点。为了减少计算量,优选地,Hough检测模块的Hough变换从对话栏的右下角开始,按照从右至左,从下至上的顺序计算,当检测到第一个圆时,输出圆心位置,并停止检测。Therefore, the function of the Hough detection module is to perform Hough transformation on the Gaussian smoothed image to detect the position of the circular emoji; only output the position of the largest emoji in the recognized emoji with coordinates x and y ; Among them, the x-axis and y-axis take the upper left corner of the dialogue bar as the zero point. In order to reduce the amount of calculation, preferably, the Hough transform of the Hough detection module starts from the lower right corner of the dialog box, and is calculated in the order from right to left and from bottom to top. When the first circle is detected, the position of the center of the circle is output, and stop detection.

在表情符号定位模块中可以获取表情符号的位置,从而可以将表情符号单独分离出来。但是到这一步系统仅仅只是知道聊天窗口出现了表情符号而已,它并不知道这个表情符号所代表的意义,所以还不能做出对应的一个响应,要实现对不同表情符号进行正确的响应,还需要识别出分离出的表情符号所代表的含义,这一过程就是表情符号识别模块所能够实现的功能。The position of the emoticon can be obtained in the emoticon positioning module, so that the emoticon can be separated separately. But up to this point, the system only knows that there is an emoji in the chat window. It does not know the meaning of the emoji, so it cannot make a corresponding response. It is necessary to identify the meanings represented by the separated emoticons, and this process is the function that the emoticon recognition module can realize.

●表情符号识别模块●Emoji recognition module

表情符号识别模块主要的思路是将定位模块所获取的表情符号图像作为模板,将包含所有默认表情符号的图像作为全局图像,然后进行模板匹配,最后找出表情符号在全局图像中的位置,由于在全局图像中包含了所有表情符号并且每个表情符号都有自己固定的位置,所以根据位置就可以确定表情符号所代表的意义了,此模块的基本流程如图10所示。The main idea of the emoticon recognition module is to use the emoticon image acquired by the positioning module as a template, and use the image containing all default emoticons as a global image, then perform template matching, and finally find out the position of the emoticon in the global image. All emoticons are included in the global image and each emoticon has its own fixed position, so the meaning of the emoticon can be determined according to the position. The basic flow of this module is shown in Figure 10.

因此表情符号识别模块包括提取模块、匹配模块和识别模块;其中,Therefore emoticon recognition module comprises extraction module, matching module and identification module; Wherein,

提取模块,用于根据表情符号定位模块输出的位置,从切割模块获得的所述对话栏的图像中获得表情符号图像,发送给匹配模块;The extraction module is used to obtain the emoticon image from the image of the dialogue column obtained by the cutting module according to the position output by the emoticon positioning module, and send it to the matching module;

匹配模块,用于将所接收的表情符号图像作为模板,将预先存储的包含所有默认表情符号的图像作为全局图像,然后进行模板匹配,最后找出表情符号图像在全局图像中的位置;The matching module is used to use the received emoticon image as a template, and use the pre-stored image containing all default emoticons as a global image, then perform template matching, and finally find out the position of the emoticon image in the global image;

识别模块,用于根据已知的全局图像中每个默认表情符号的位置范围和表情含义,判断所述匹配模块找出的表情符号图像的位置对应哪个表情含义,将表情含义发送给响应模块。The identification module is used to determine which expression meaning the position of the emoticon image found by the matching module corresponds to according to the position range and expression meaning of each default emoticon in the known global image, and send the expression meaning to the response module.

仍以QQ为例,图11是QQ所有的默认表情符号截图。Still taking QQ as an example, Figure 11 is a screenshot of all the default emoticons of QQ.

从图中可以看出一共有8行14列表情符号,共计105个,每个表情符号都占有一个固定的位置,并且都有一个固定的外接矩形,经过测量得到表情符号矩形所占的区域大小为33×33像素,这里就可以将图11划分成112个小矩形区域,每个区域代表一个表情符号,要想识别表情符号只需判断模板匹配中返回的表情符号的坐标落在哪个区域即可,例如:It can be seen from the figure that there are 8 rows and 14 columns of emoticons, a total of 105 emoticons, each emoticon occupies a fixed position, and has a fixed circumscribed rectangle. After measurement, the area occupied by the emoji rectangle is obtained. is 33×33 pixels, here we can divide Figure 11 into 112 small rectangular areas, and each area represents an emoji. To recognize an emoji, you only need to judge which area the coordinates of the emoji returned in template matching fall in. Yes, for example:

微笑表情符号的区域为0<x<33,0<y<33。The area of the smiling emoji is 0<x<33, 0<y<33.

撇嘴表情符号的区域为33<x<66,0<y<33。The region of curling mouth emoji is 33<x<66, 0<y<33.

惊讶表情符号的区域为0<x<33,33<y<66。The region of the surprised emoji is 0<x<33, 33<y<66.

难过表情符号的区域为33<x<66,33<y<66。The region of sad emoji is 33<x<66, 33<y<66.

匹配结果如图12所示,为了方便观察识别结果,这里将待识别表情符号的图像和所有默认表情符号的图像以及识别结果的输出一起显示了出来,并且用线条标识了模板匹配的结果,可见利用该方法可以成功的进行模板匹配并且利用位置识别出表情符号的含义。The matching results are shown in Figure 12. In order to facilitate the observation of the recognition results, the images of the emoticons to be recognized are displayed together with the images of all default emoticons and the output of the recognition results, and the results of the template matching are marked with lines, which can be seen Using this method, template matching can be successfully performed and the meaning of emoticons can be recognized by using the location.

●响应模块●Response module

响应模块比较理想的响应方式是具有准确性和一定的趣味性,也就是说该模块应该能够准确的做出与表情符号所对应的响应,让用户很容易就能理解到响应的含义,并且要求一定的趣味性,这样可以提高用户体验。The ideal response mode of the response module is accurate and interesting, that is to say, the module should be able to accurately respond to the emoticons, so that users can easily understand the meaning of the response, and require A certain amount of fun can improve the user experience.

该响应模块在论文研究初期的计划是寻找一种特制的外设,该外设应该具有以下特性:The plan for this response module at the beginning of the dissertation research was to find a purpose-built peripheral that should have the following characteristics:

1)可以模仿人脸做出喜怒哀乐等各种表情。1) It can imitate human faces to make various expressions such as joy, anger, sorrow and joy.

2)可以用某种方式连接到用户的主机上,与用户主机进行通信。2) It can be connected to the user's host in some way, and communicate with the user's host.

3)能够通过编程来控制该外设做出不同的表情。3) It can be programmed to control the peripheral to make different expressions.

传输方式可以根据实际需要来选择,传输的数据的内容应该做如下设计,在识别模块已经将105个表情符号进行了编号,识别的结果就是表情符号的编号,所以可以将表情机器人的状态也进行编号,这个编号应该和表情符号的编号一致。这样只需要将编号发送给响应模块,就可以做出对应的表情响应了,所以传送的数据内容可以设计成1到105之间的整数,当响应模块收到编号,就可以改变到对应的状态,那么该状态正好就是表情符号对应的状态。The transmission method can be selected according to actual needs. The content of the transmitted data should be designed as follows. In the recognition module, 105 emoticons have been numbered, and the recognition result is the number of the emoticon, so the state of the emoticon robot can also be carried out. Number, this number should be consistent with the number of the emoji. In this way, you only need to send the number to the response module, and then you can make a corresponding expression response, so the content of the transmitted data can be designed as an integer between 1 and 105. When the response module receives the number, it can change to the corresponding state , then the state is exactly the state corresponding to the emoji.

综上所述,以上仅为本发明的较佳实施例而已,并非用于限定本发明的保护范围。凡在本发明的精神和原则之内,所作的任何修改、等同替换、改进等,均应包含在本发明的保护范围之内。To sum up, the above are only preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims (5)

1.一种基于即时通讯工具的表情机器人,其特征在于,包括聊天窗口监测模块、表情符号定位模块、表情符号识别模块和响应模块;1. A facial expression robot based on an instant messaging tool, comprising a chat window monitoring module, an emoticon location module, an emoticon recognition module and a response module; 所述聊天窗口监测模块,用于在确定当前焦点窗口是即时通讯工具的聊天窗口后,对所述聊天窗口进行监测,定时或当用户有新的聊天消息显示出来时,将聊天窗口的图像截取下来,并保存为图片;The chat window monitoring module is used to monitor the chat window after determining that the current focus window is the chat window of the instant messaging tool, and intercept the image of the chat window regularly or when a new chat message is displayed by the user down, and save as a picture; 所述表情符号定位模块,用于分析聊天窗口监测模块所截取下来的图片,寻找其中的表情符号,找到表情符号之后,将表情符号的位置发送给所述表情符号识别模块;The emoticon positioning module is used to analyze the pictures intercepted by the chat window monitoring module, find the emoticons therein, and after finding the emoticons, send the position of the emoticons to the emoticon recognition module; 所述表情符号识别模块,用于当接收到表情符号定位模块发过来的表情符号的位置后,将该位置的表情符号与已知表情符号库中的表情符号进行对比,从而确定该表情符号所代表的意义,然后将结果发送给响应模块;The emoticon recognition module is used to compare the emoticon at the position with the emoticon in the known emoticon library after receiving the position of the emoticon sent by the emoticon positioning module, so as to determine the location of the emoticon. The meaning of the representative, and then send the result to the response module; 所述响应模块,用于在接收到表情符号识别模块发送过来的结果后,通过设定的表现方法进行响应。The response module is used for responding through the set expression method after receiving the result sent by the emoticon recognition module. 2.如权利要求1所述的表情机器人,其特征在于,所述响应模块通过声音、图像和/或动作进行响应。2. The facial expression robot according to claim 1, wherein the response module responds through sound, image and/or action. 3.如权利要求1所述的表情机器人,其特征在于,所述表情符号定位模块包括切割模块、灰度化模块、平滑模块和哈夫Hough检测模块:3. expression robot as claimed in claim 1, is characterized in that, described emoticon location module comprises cutting module, graying module, smoothing module and Hough Hough detection module: 切割模块,用于根据对话栏在聊天窗口中的位置,从聊天窗口的图像中将对话栏的图像切割出来,将切割出来的图像发送给灰度化模块;The cutting module is used to cut out the image of the dialogue bar from the image of the chat window according to the position of the dialogue bar in the chat window, and send the cut image to the grayscale module; 灰度化模块,用于将所接收的图像进行灰度化出来,得到灰度图,发送给平滑模块;The grayscale module is used to grayscale the received image to obtain a grayscale image and send it to the smoothing module; 平滑模块,用于对接收到的灰度图进行高斯平滑处理;A smoothing module is used to perform Gaussian smoothing on the received grayscale image; Hough检测模块,用于对高斯平滑处理后的图像进行Hough变换,检测出圆形的表情符号所在的位置;只输出识别出的表情符号中坐标x、y都是最大的表情符号的位置;其中x轴、y轴以对话栏的左上角为零点。The Hough detection module is used to carry out Hough transform to the image after Gaussian smoothing, and detects the position of the circular emoticon; only outputs the position where coordinates x and y are the largest emoticon in the emoticon recognized; wherein The x-axis and y-axis take the upper left corner of the dialogue bar as the zero point. 4.如权利要求3所述的表情机器人,其特征在于,所述Hough检测模块的Hough变换从对话栏的右下角开始,按照从右至左,从下至上的顺序计算,当检测到第一个圆时,输出圆心位置,并停止检测。4. The emoticon robot according to claim 3, wherein the Hough transform of the Hough detection module starts from the lower right corner of the dialogue column, and calculates in the order from right to left and from bottom to top, when the first When a circle is formed, the position of the center of the circle is output and the detection is stopped. 5.如权利要求3或4所述的表情机器人,其特征在于,所述表情符号识别模块包括提取模块、匹配模块和识别模块;5. the expression robot as claimed in claim 3 or 4, is characterized in that, described emoticon recognition module comprises extraction module, matching module and identification module; 所述提取模块,用于根据表情符号定位模块输出的位置,从切割模块获得的所述对话栏的图像中获得表情符号图像,发送给匹配模块;The extraction module is used to obtain the emoticon image from the image of the dialogue column obtained by the cutting module according to the position output by the emoticon positioning module, and send it to the matching module; 所述匹配模块,用于将所接收的表情符号图像作为模板,将预先存储的包含所有默认表情符号的图像作为全局图像,然后进行模板匹配,最后找出表情符号图像在全局图像中的位置;The matching module is used to use the received emoticon image as a template, and pre-stored images containing all default emoticons as a global image, then perform template matching, and finally find out the position of the emoticon image in the global image; 所述识别模块,用于根据已知的全局图像中每个默认表情符号的位置范围和表情含义,判断所述匹配模块找出的表情符号图像的位置对应哪个表情含义,将表情含义发送给响应模块。The recognition module is used to judge which expression meaning corresponds to the position of the emoticon image found by the matching module according to the position range and expression meaning of each default emoticon in the known global image, and send the expression meaning to the response module.
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Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103914005A (en) * 2012-12-31 2014-07-09 北京新媒传信科技有限公司 Robot control method and terminal
CN104680166A (en) * 2013-11-27 2015-06-03 施耐德电器工业公司 Information identification method and information identification device
CN104699662A (en) * 2015-03-18 2015-06-10 北京交通大学 Method and device for recognizing whole symbol string
CN105204748A (en) * 2014-06-27 2015-12-30 阿里巴巴集团控股有限公司 Terminal interaction method and device
CN106228156A (en) * 2016-07-18 2016-12-14 百度在线网络技术(北京)有限公司 A kind of method and apparatus determining information alert content
CN106445478A (en) * 2015-08-12 2017-02-22 腾讯科技(深圳)有限公司 Graphic expression conversion method and apparatus
CN106530096A (en) * 2016-10-08 2017-03-22 广州阿里巴巴文学信息技术有限公司 Emotion icon processing method, device and electronic apparatus
CN108268583A (en) * 2017-08-21 2018-07-10 广州市动景计算机科技有限公司 The method and apparatus of emoticon meaning displaying
CN110689009A (en) * 2019-09-18 2020-01-14 北京三快在线科技有限公司 Information identification method and apparatus, electronic device and computer-readable storage medium
CN111597966A (en) * 2020-05-13 2020-08-28 北京达佳互联信息技术有限公司 Expression image recognition method, device and system
CN112784293A (en) * 2019-11-08 2021-05-11 游戏橘子数位科技股份有限公司 Recording notification method for picture capture

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101494618A (en) * 2008-11-28 2009-07-29 腾讯科技(深圳)有限公司 Display system and method for instant communication terminal window
CN102289339A (en) * 2010-06-21 2011-12-21 腾讯科技(深圳)有限公司 Method and device for displaying expression information

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101494618A (en) * 2008-11-28 2009-07-29 腾讯科技(深圳)有限公司 Display system and method for instant communication terminal window
CN102289339A (en) * 2010-06-21 2011-12-21 腾讯科技(深圳)有限公司 Method and device for displaying expression information

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
崔忠艾: "聊天工具仿真表情插件的设计与实现", 《中国优秀硕士学位论文全文数据库 信息科技辑》, 30 September 2010 (2010-09-30), pages 9 - 54 *

Cited By (18)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103914005A (en) * 2012-12-31 2014-07-09 北京新媒传信科技有限公司 Robot control method and terminal
CN104680166A (en) * 2013-11-27 2015-06-03 施耐德电器工业公司 Information identification method and information identification device
CN105204748A (en) * 2014-06-27 2015-12-30 阿里巴巴集团控股有限公司 Terminal interaction method and device
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
CN104699662A (en) * 2015-03-18 2015-06-10 北京交通大学 Method and device for recognizing whole symbol string
CN104699662B (en) * 2015-03-18 2017-12-22 北京交通大学 The method and apparatus for identifying overall symbol string
CN106445478A (en) * 2015-08-12 2017-02-22 腾讯科技(深圳)有限公司 Graphic expression conversion method and apparatus
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
CN106228156A (en) * 2016-07-18 2016-12-14 百度在线网络技术(北京)有限公司 A kind of method and apparatus determining information alert content
CN106530096A (en) * 2016-10-08 2017-03-22 广州阿里巴巴文学信息技术有限公司 Emotion icon processing method, device and electronic apparatus
CN108268583A (en) * 2017-08-21 2018-07-10 广州市动景计算机科技有限公司 The method and apparatus of emoticon meaning displaying
CN108268583B (en) * 2017-08-21 2022-06-14 阿里巴巴(中国)有限公司 Method and equipment for displaying emoticon meanings
CN110689009A (en) * 2019-09-18 2020-01-14 北京三快在线科技有限公司 Information identification method and apparatus, electronic device and computer-readable storage medium
CN110689009B (en) * 2019-09-18 2021-09-07 北京三快在线科技有限公司 Information identification method and apparatus, electronic device and computer-readable storage medium
CN112784293A (en) * 2019-11-08 2021-05-11 游戏橘子数位科技股份有限公司 Recording notification method for picture capture
CN112784293B (en) * 2019-11-08 2024-06-04 游戏橘子数位科技股份有限公司 Method for recording notice of picture acquisition
CN111597966A (en) * 2020-05-13 2020-08-28 北京达佳互联信息技术有限公司 Expression image recognition method, device and system
CN111597966B (en) * 2020-05-13 2023-10-10 北京达佳互联信息技术有限公司 Expression image recognition method, device and system

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