...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Biometrics, IET >Heart-ID: human identity recognition using heart sounds based on modifying mel-frequency cepstral features
【24h】

Heart-ID: human identity recognition using heart sounds based on modifying mel-frequency cepstral features

机译：Heart-ID：基于修改mel-频率倒谱特征的使用心音的人类身份识别

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This study presents a new framework for human identity recognition using heart sound signals. The proposed framework is based on extracting cepstral features from heart sound signals, which are known as phono-cardio-gram (PCG). Two well-known cepstral features have been adopted in most of the previously implemented PCG biometric authentication systems; namely, mel-frequency and linear frequency cepstral features. In this study, two more cepstral features are proposed based on modifying the mel-frequency cepstral features. The first one is based on modifying the mel-frequency equation to increase the non-linearity of the triangular filters in the frequency range of the PCG signal. The other is based on replacing mel-scaled triangular filters with wavelet packet filters where a non-linear filter bank structure is designed using wavelet packet decomposition to select the appropriate bases for extracting discriminant features. The proposed system uses wavelet de-noising for pre-processing and linear discriminant analysis for classification. The proposed system is evaluated on two databases; one consists of 21 users (BioSec. database) and the other consists of 206 users (HSCT-11 database). Moreover, the proposed system is compared with previous systems that used the same databases. On the basis of the achieved results over the two databases, the two proposed cepstral features achieved higher correct recognition rates and lower error rates in identification and verification modes, respectively.
机译：这项研究提出了使用心音信号进行人类身份识别的新框架。所提出的框架基于从心音信号中提取倒谱特征的过程，这就是所谓的心音图（PCG）。在大多数先前实施的PCG生物特征认证系统中，已经采用了两个众所周知的倒谱特性。即梅尔频率和线性频率的倒谱特征。在这项研究中，基于修改mel频率倒谱特征，提出了另外两个倒谱特征。第一个基于修改mel-频率方程，以增加PCG信号频率范围内三角滤波器的非线性。另一种方法是用小波包滤波器替换mel比例三角形滤波器，其中使用小波包分解设计非线性滤波器组结构，以选择合适的基础来提取判别特征。提出的系统使用小波消噪进行预处理，并使用线性判别分析进行分类。提议的系统在两个数据库上进行评估；一个由21个用户（BioSec。数据库）组成，另一个由206个用户（HSCT-11数据库）组成。此外，将提出的系统与使用相同数据库的先前系统进行了比较。根据在两个数据库上获得的结果，两个建议的倒谱特征分别在识别和验证模式下实现了较高的正确识别率和较低的错误率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号