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基于手势识别的文字输入系统 被引量:2

Text input system based on gesture recognition
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摘要 基于视觉的手势识别是实现新一代人机交互的关键技术。通过手势识别向屏幕输入文字以供搜索查找的系统基本没有,在现有的手势识别基础上,利用汉语字母和数字对应的手语作为输入手势,采用微软的kinect获取深度图像,对其进行手势分割。通过Canny算法提取手势的边缘,利用小波矩提取特征,得到手势字母,实现了具有手势识别以及基于文字输入功能的系统。实验表明该系统能够准确有效地实现汉字的输入。 Vision-based gesture recognition is a key technique to achieve a new generation of human-computer interaction.As few text input search system by gesture recognition is developed, based on the existing gesture recognition techniques,this paper uses the gestures which are corresponding to the Chinese letters and numbers as input gesture and uses Microsoft kinect to obtain depth image to conduct hand gesture segmentation. The edge of the gesture is extracted by Canny algorithm,and then the feature is extracted based on wavelet moment. The gesture letters are obtained. It achieves the text input system based on gesture recognition. Experiments show that the system is able to achieve Chinese characters accurately and effectively.
出处 《计算机工程与应用》 CSCD 北大核心 2015年第3期66-68,142,共4页 Computer Engineering and Applications
基金 安徽省自然科学基金青年基金项目(No.11040606Q07) 高校省级重点自然科学研究项目(No.kj2010A023) 安徽大学青年科学研究基金(No.2009QN0019B) 安徽大学青年骨干教师培养对象经费资助
关键词 CANNY算法 手势识别 小波矩 文字输入系统 Canny algorithm gesture recognition moment compare text input system
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参考文献14

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二级参考文献149

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