Automatic Recognition of Basic Strokes Based on FMCW Radar System
发布时间：2021-06-28
点击次数：
影响因子：3.193
DOI码：10.1109/JSEN.2021.3071884
发表刊物：IEEE SENSORS JOURNAL
关键字：Basic strokes classification, FMCW radar, CNN, Feature extraction
摘要：—It has been demonstrated the advantage of basic stroke recognition algorithm in the field of human computer interaction (HCI). However, most traditional techniques heavily rely on the touch-contact operations to obtain character information, which limits the further application in non-contact scenario such as erm infection environment, high/low temperature environment or cene for blind human. This paper proposes a non-contact and automatic basic stroke recognition algorithm for handwritten Chinese characters based on frequency modulated continuous wave (FMCW) radar system. First, the radar system collects intermediate frequency (IF) signal of the eight basic strokes given as follows: ー (horizontal stroke), 丶 (dot stroke), ㇀ (lift stroke), ノ (left falling stroke), 丿 (bend stroke), 乀 (right falling stroke), 丨 (vertical stroke) and 亅(hook stroke). Second, a range-time sequence (RTS) is obtained from IF signal by the window Fast Fourier Transform (window-FFT) algorithm, and an azimuth-time sequence (ATS) is obtained from IF signal by the frequency omain Capon (FD-Capon) algorithm. Then, the feature area framing, binarization and open operation (FA-FBO) algorithm is proposed to enhance the features of the above two sequences. After that, a feature map set containing RTS feature map (RTSFM) and ATS feature map (ATSFM) is obtained. Finally, a novel convolutional neural network (CNN) model is customized to perform the strokes classification task with these feature maps as input. Experimental results demonstrate that the proposed scheme is able to effectively recognize the eight basic strokes and achieve an average classification accuracy of 99.25%.
合写作者：徐龙
第一作者：雷文太
论文类型：期刊论文
论文编号：10.1109/JSEN.2021.3071884
学科门类：工学
一级学科：信息与通信工程
文献类型：J
卷号：21
期号：13
页面范围：15101-15113
是否译文：否
发表时间：2021-06-01
收录刊物：SCI、EI