期刊
IEEE SENSORS JOURNAL
卷 23, 期 15, 页码 16900-16906出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2023.3286255
关键词
Biometrics; fiber Bragg gratings (FBGs); footprints; pattern recognition; support vector machine (SVM)
This paper proposes a biometric identification system based on plantar pressure, using fiber Bragg gratings to detect footprint patterns, and a support vector machine for classification. The pattern recognition system achieved a recognition rate of over 86% for 12 different stepping patterns.
Biometric recognition based on physiological characteristics has been widely used for security reasons. In these systems, unique features, such as fingerprints, iris patterns, face structure, and voice, are used to recognize a person instead of codes that can be easily transferred. The biometric identification system based on plantar pressure proposed in this work applies a support vector machine (SVM) procedure to classify footprint patterns detected by a platform instrumented with fiber Bragg gratings (FBGs). Two sets of seven in-series gratings, with Bragg wavelengths within the 1526.96- and 1553.86-nm range, delimit two sensing regions corresponding to the left and right footprints. The coupled and nonlinear responses provided by the sensors are preprocessed and organized in a matrix. An algorithm based on SVM was used to extract and recognize foot features. The pattern recognition system constructed in this way returned hit rates greater than 86% for 12 classes, corresponding to different stepping patterns, with data not belonging to the training set.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据