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空中手写字符识别系统研究
其他题名Research on Writting-in-the-air Handwritten Character Recognition System
靳潇杰
学位类型工学硕士
导师刘成林
2014-06-04
学位授予单位中国科学院大学
学位授予地点中国科学院自动化研究所
学位专业模式识别与智能系统
关键词视觉手势字符 联机字符串识别 删除几何模型 手指轨迹跟踪 Visual Gesture Character String Online Character String Recognition Deletion Geometric Models Fingertip Trajectory Capturing
摘要文字作为人类社会中广泛使用的信息传播和交流工具,在人机交互系统中扮演着重要的角色。目前常用的文字输入方式包括:键盘,手写板,平板电脑等。这些输入方式都存在着各自的缺点,如键盘受到大小和按键数量的限制,手写板等设备受到体积大小的限制,书写区域有限。因此设计更自然,更方便,更高效的文字输入方式是一个重要的研究方向。近年来,人们通过将手写文字识别和计算机视觉系统结合设计了一类基于视觉手势的文字输入方式。其中一种途径是人们正常使用纸笔书写然后通过摄像头采集纸上的书写墨迹,将其识别为文字。这种方法仍然受到了外部条件(纸张的大小等)的限制。另一种途径则是直接通过手指在桌面或空中书写虚拟文字,使用摄像头或运动传感器如Kinect等实时采集手指的移动轨迹,之后将轨迹识别为文字。由于在此类系统中很难判断书写中的提笔/落笔操作,导致字间切分十分困难,所以目前这类系统只能识别单个文字。 针对目前空中手写字符串识别的研究仍是空白的现状,本文提出了一种新颖的空中手写字符串识别方法,用户使用手指在空中书写,通过摄像头或运动传感器采集手指移动轨迹,之后将轨迹识别为字符串。本文主要工作包括以下几个方面: (1) 搭建了基于Kinect的手指书写轨迹采集系统。收集了由30人书写包含1000个空中手写数字串数据库。 (2) 针对空中手写字符串中缺少提笔/落笔信息,导致字符串过切分后存在多余笔划的问题,提出了笔划段的一元/二元删除几何模型用于计算笔划段的删除代价。 (3) 在集成切分-识别的框架下,通过有效融合字符识别器输出、字符几何模型以及笔划段删除几何模型以有效去除多余笔划段,从而提高字符串切分和识别的准确率。 (4) 经过在收集的数据库上测试,本文提出的方法得到了较好的识别率:字符串水平整串识别正确率大于80%,且识别性能显著优于基于HMM的方法,从而验证了本文方法的有效性。
其他摘要As a widely used tool for information transmission and communication in human society, text plays an important role in the design of human-computer interaction system. Currently, common text input methods include keyboard, writing pad and tablet computer, etc, all of which have disadvantages, such as the keyboard is limited by the size and key number and the writng pad’s writing area is small. Thus, it attracts lots of interests to design natural, convenient and efficient text input methods. In recent years, by combining handwriting recognition and computer vision techniques, researchers have developed a class of vision gesture based text input systems, which can be divided into two categories. In one category, handwriting was produced with an ordinary pen on paper and a camera was used to capture the ink trajectory, which was recognized into text. Such systems were still limited to some external conditions, such as the size of writing area. In the other category, the characters were written by moving a finger on the desk or in the air. The finger trajectory was recorded by a camera or other motion sensors, e.g., Kinect. Since there is no pen lift information in the moving trajectory, it complicates the segmentation of characters, and so, these systems can only recognize isolated characters. This dissertation reports our first attempt to gesture character string recognition. In our system, a user can write freely in the air by moving his/her finger with the trajectory captured by a camera or a motion sensor, such as Kinect, then, the written-in-the-air trajectory is recognized into string result. The major contributions of this dissertation are as follows: (1) To perform experiment, we build a Kinect-based fingertip trajectory capturing system and collect 1,000 gesture digit strings written by 30 persons. (2) To solve the problem that there are extra stokes after over-segmentation due to the lack of pen lift information in the visual gesture strings, we propose deletion geometric models for deleting stroke segments that are likely to be ligatures. (3) To improve the accuracy of character string segemtation and recognition, we integrate character classifier output, character geometric model and deletion geometric model in the integrated segmentation-recognition framework. (4) By performing experiments in our collected gesture digit string dataset, our method achieves promising results: the string-level correct rate is over 80%. What’s more, our method...
其他标识符201128014628039
语种中文
文献类型学位论文
条目标识符http://ir.ia.ac.cn/handle/173211/7727
专题毕业生_硕士学位论文
推荐引用方式
GB/T 7714
靳潇杰. 空中手写字符识别系统研究[D]. 中国科学院自动化研究所. 中国科学院大学,2014.
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