数字时代

输入字符不用按键的虚拟键盘 Senseboard推出的可以戴在手上的虚拟键盘没有任何按键,全凭侦测人手部的活动判断输入的字符。由于根本没有按键,这种键盘真正实现了零噪音,任何场合都不会影响到别人。该公司表示,该款键盘的输入速度能够达到普通键盘的速度。     

基于数字图像处理的虚拟输入方法

针对当前嵌入式设备输入方法存在的高成本低体验问题,提出了一种运行于嵌入式系统中基于数字图像处理的虚拟输入方法.该方法利用嵌入式设备附加的摄像设备,对用户在虚拟键盘上的按键过程进行图像采集,通过角点识别和图像分割进行按键识别,以便通过采集到的图像定位出用户点击的目标按键,从而实现信息输入过程.通过实例验证了该方法的可行性...     

智能断电更节省——摩天手X100无线键鼠套装

摩天手X100超薄多媒体无线键鼠套装是一款性价比很高的入门级无线套装产品,由超薄多媒体键盘和智能光电无线鼠标组成。键盘采用深色调的银灰色和黑色搭配,按键布局采用紧凑式设计,不过常规字母按键布局并没有紧缩,而是对功能键和方向键进行了重新布局,这样在尽可能不影响输入速度和输入习惯的情况下,实现了键盘体积的轻薄和小巧。     

模拟键盘按键 自动输入文字

键盘对于每个操作电脑的人员来说是最熟悉不过的了。键盘上的按键可分为两类:按下后会在电脑的输入窗口上出现对应字符的按键,如字母键和数字键等,我们称之为字符键;按下后虽然看不到字符但会产生控制作用的按键,如回车键、光标键等,我们称之为控制键。对于程序员来说,键盘上的每个按键都一样,无非是不同按键产生的键盘扫描码不同。在不同的操作系统下,键盘扫描码常常被转换为不同的编码以方便应用程序调用,比如在DOS系统下的ASCⅡ码,在Windows系统下的虚拟键盘码等等。 有时我们希望能以程序的方式模拟键盘按键,以达到自动输入文字或者控制操作的目的。在DOS系统下通常使用中断调用,产生键盘的扫描码的方法来实现。在Windows系统下,由于Windows本身的一些限制和特点,一般不直接使用中断调用。了解一点Windows编程的朋友应该知道,     

基于摄像头的手势控制系统的设计与实现

采用WIA(或DirectShow等流媒体处理技术)技术,以普通家用PC机为硬件开发平台,采用WINDOWS XP操作系统,并通过外接调用摄像头功能对有效目标进行捕获,它主要是利用原创的设计并实现颜色识别跟踪算法、动作轨迹的判断和识别算法,通过代码控制操纵键盘的技术来实现手势控制这一功能。该系统具有无接触式动作识别功能,有效地代替了鼠标控制其他程序的基本功能。更重要的是,它免去了通过鼠标键盘输入某些控制指令的同时,还能结合后台虚拟按键控制其他程序运行。     

利用单片机A/D端口扩展键盘的一点改进

键盘是单片机人机对话中最常用的输入设备,因此,采用简单的方法,使用最少的口线来扩展更多的按键,可以有效地节省单片机资源。在本刊2001年第8期《利用单片机A/D端口扩展键盘的方法》一文中,作者介绍了一种利用A/D端口及分压电路扩展键盘的方法。笔者根据以往的实践,对该方法提出一些改进,使其实现起来更简单,控制的按键更多,按键识别更准确。     

基于手势识别算法的鼠标终端

提出了一种基于静态手势与动态手势的识别算法,并结合Windows API的鼠标类函数实现鼠标操作.首先,通过图像处理技术把从摄像头捕捉的原图像转换为可信度较高的二值图像;其次,调用静态手势识别算法识别展开的手指个数,根据手指个数,结合Windows API的鼠标类函数实现鼠标双击及移动功能;最后,当检测到手指个数为5时,调用动态手势识别算法来识别手势的上下左右四个方向,并结合Windows API的鼠标类函数模拟鼠标左右键按下、抬起及滚轮滑动等操作.实验表明,该手势识别算法的识别率达到了94.11%,对于一些开发平台没有鼠标或在使用鼠标不方便的情况下,用手势来替代鼠标输入具有一定的研究价值和意义.     

智能硬币储蓄罐设计

普通硬币储蓄罐只具备存储硬币的功能,提出一种智能硬币储蓄罐,能够对硬币自动分拣,分别存储,同时可以根据输入金额,自动出币。智能硬币储蓄罐以STM32单片机为控制核心,包括LCD1602显示屏、矩阵键盘、电机、光电传感器、存储仓、Wi-Fi模块等模块组成。实现了不同面值硬币的自动分类、计数与存取,罐内硬币数量的显示。通过穷举算法,实现最优的出币方式。提高了储蓄罐的智能化,具有一定的应用价值。     

键盘接口

一、一般原理 键盘是人和机器的交界处,起着人向机器传递信息的重要作用。它和打印机、显示器组成的终端设备以及和软盘等组成的输入机广泛应用于计算机系统。 键盘的基本功能是通过操作员按键、将键开关信息经过编码电路转换成系统可以接收的二进制字符编码信息,然后输入计算机。 早期的键盘通过机械编码条实现信息的转换,由于这种键盘是靠机械部件的动作来进行的,因而可靠性比较差。现在都采用电子式键盘,其中干簧键是最早使用的,它是由干簧管和磁环组成的触点开关。霍耳键是利用霍耳效     

智能仪器的非编码键盘接口

在智能仪器设计中,一般采用键盘作输入器件。由于键盘工作可靠、寿命长、可控制、设计灵活等优点,在智能仪器中应用很广。本文即介绍各种非编码键盘的硬件接口和软件查找按键的方法及其特点。为说明方便,以下均以3×3键盘为例说明。一、硬件接口方法 1.常用的键盘接口要求常见的键盘接口见图1,其中R的最大值由下式决定:     

随机数字密码键盘的设计

针对传统键盘的键盘值固定、保密性和安全性差的缺点,在传统密码键盘的基础上,设计了一种随机数字密码键盘,使传统键盘增加了新的功能特性,即在数字键盘上增加了十个数码管来显示0至9十个数字,并通过单片机设计时钟中断程序产生随机数使数码管随机显示十个数字。通过数字位置的随机变化,即使他人观察到了用户的手势,仍无法通过判断键位获取密码,因此用户可以放心地在键盘面前输入密码,不用担心手势泄露密码,从而大大地提高了密码输入的安全性,在根源上杜绝了密码盗窃犯罪的可能。     

数字家庭环境中双手交互技术研究

采用基于视觉的双手手势控制方法,构建数字家庭环境。在获取肤色图像后,通过面积过滤和图像方位分辨出左右手的位置,使用形状过滤算法识别出指尖的位置。分析左手静态手势判断所控制的家电,同时跟踪右手指尖移动的路径,通过方向离散化得到方向向量,使用Baum-Welch算法训练方向向量,用Viterbi算法识别动态手势,实现家电状态的控制。实验结果表明,该方法能有效地在数字家庭环境中完成普通家电的控制功能。     

基于MEMS加速度传感器的智能输入系统

如今在使用大尺寸显示器的PC应用领域,传统输入设备键盘、鼠标以及触摸屏使用的不便已愈加凸显.针对这一问题,设计了基于MEMS加速度传感器的智能输入系统,同时也提出了一个新颖的人机交互理念.并且针对系统应用的特点,文中还提出了一种简单而有效的识别算法,以实现对手部动作的识别,从而帮助使用者以更加舒适的肢体语言对PC进行操作.该系统可以很好实现音乐、电影播放,图片、长文档浏览,幻灯片演示等应用的控制并可实现鼠标的全部功能,尤其当被使用于多媒体领域,将更具价值.     

A novel approach for dynamic hand gesture recognition using contour-based similarity images

A novel approach is proposed for the recognition of moving hand gestures based on the representation of hand motions as contour-based similarity images (CBSIs). The CBSI was constructed by calculating the similarity between hand contours in different frames. The input CBSI was then matched with CBSIs in the database to recognize the hand gesture. The proposed continuous hand gesture recognition algorithm can simultaneously divide the continuous gestures into disjointed gestures and recognize them. No restrictive assumptions were considered for the motion of the hand between the disjointed gestures. The proposed algorithm was tested using hand gestures from American Sign Language and the results showed a recognition rate of 91.3% for disjointed gestures and 90.4% for continuous gestures. The experimental results illustrate the efficiency of the algorithm for noisy videos.     

采用AT89c52的乱序键盘设计

The password keyboard as a kind of input device that is essential to bank and other financial departments,it must have high credibility,safety,and the function of keeping secret.Disorder keyboard is a developed kind on the basis of the traditional password keyboard,which increased some new functions and characteristics,for example,there is LED on the surface of the keys,and the numbers displayed on the keys are random,also a certain angle of view is restricted.Outside of a certain angle,the number LED displayed on the keyboard is impossible to be seen.Even other people can see the keys that the customer pressed,but because when the customer finished inputting the password,the key numbers will be re-arranged again,so,the customer unnecessarily worried about that other people would take his password.     

Gestures that people can understand and use

Recent advances in computing devices push researchers to envision new interaction modalities that go beyond traditional mouse and keyboard input. Typical examples are large displays for which researchers hope to create more “natural” means of interaction by using human gestures and body movements as input. In this article, we reflect about this goal of designing gestures that people can easily understand and use and how designers of gestural interaction can capitalize on the experience of 30 years of research on visual languages to achieve it. Concretely, we argue that gestures can be regarded as “visual expressions to convey meaning” and thus are a visual language. Based on what we have learned from visual language research in the past, we then explain why the design of a generic gesture set or language that spans many applications and devices is likely to fail. We also discuss why we recommend using gestural manipulations that enable users to directly manipulate on-screen objects instead of issuing commands with symbolic gestures whose meaning varies among different users, contexts, and cultures.     

A multilevel input system with force-sensitive elements

Force-sensitive multilevel input elements are introduced as the basic building blocks for compact-size input devices in mobile environments. Compared with switch-type keys, multilevel elements can decrease the number of keys on a keyboard while maintaining the input capacity. A multilevel input mechanism using force-sensitive sensor pads is demonstrated in a three-level three-element tactile chording system with multimodal feedback. Two schemes are introduced to segment the output range of the sensor into levels. For relatively unpracticed users, the scheme based on maximum finger forces gives an average error rate of 20.2% and an input time of 2.24 s for a chord of three inputs. Reclassification of the experimental data using Gaussian segmentation shows that significant improvement of the performance can be expected.     

基于Linux的智能终端键盘驱动的研究与实现

以OMAP5912双核处理器为核心硬件平台,利用其丰富的外围接口,在Montavista Linux环境下,研究并实现了矩阵键盘输入设备的驱动支持,进一步提高了智能终端的人机交流程度。     

A comparative study of gestural, keyboard, and mouse interfaces

This paper presents results from three experiments which compared gestural, keyboard, and mouse/keyboard interfaces to a spreadsheet program. This is the first quantitative comparison of these types of interfaces known to the author. The gestural interface employed gestures (hand-drawn marks such as carets or brackets) for commands, and handwriting as input techniques. In one configuration, the input/output hardware consisted of a transparent digitizing tablet mounted on top of an LCD which allowed the user to interact with the program by writing on the tablet with a stylus. The experiments found that participants were faster with the gestural interface than with the keyboard or mouse/keyboard interface. In addition, subjects tended to prefer the gestural interface over the keyboard interface. Inexperienced mouse users also tended to prefer the gestural interface over the mouse/keyboard interface, although experienced mouse users preferred the mouse. The main difficulties with the gestural interface had to do with poor display legibility and problems with the stylus. The benefits of the gestural interface are explained in terms of the fewer number of steps required to carry out an operation, the greater ease of remembering gestural commands, and the ability to focus on a single surface for input and output.