电子学报 ›› 2015, Vol. 43 ›› Issue (1): 185-190.DOI: 10.3969/j.issn.0372-2112.2015.01.029

• 科研通信 • 上一篇    下一篇

利用抗噪纹理特征的快速鸟鸣声识别

魏静明, 李应   

  1. 福州大学数学与计算机科学学院, 福建 福州 350108
  • 收稿日期:2013-06-09 修回日期:2014-05-06 出版日期:2015-01-25
    • 作者简介:
    • 魏静明 男, 1988年11月出生, 河南新乡人.2014年3月毕业于福州大学数学与计算机科学学院, 工学硕士, 读研期间主要研究方向为声音识别.E-mail:wjm3219@yeah.net;李应 男, 1964年8月出生, 福建福州闽清人.现为福州大学数学与计算机科学学院教授, 主要研究方向为环境声音识别、信息安全.E-mail:fj_liying@fzu.edu.cn
    • 基金资助:
    • 国家自然科学基金 (No.61075022)

Rapid Bird Sound Recognition Using Anti-Noise Texture Features

WEI Jing-ming, LI Ying   

  1. College of Mathematics and Computer Science, Fuzhou University, Fuzhou, Fujian 350108, China
  • Received:2013-06-09 Revised:2014-05-06 Online:2015-01-25 Published:2015-01-25

摘要:

针对非平稳噪声下的鸟鸣声识别问题,提出一种利用抗噪纹理特征的快速鸟鸣声识别方法,该方法也解决了纹理特征提取过程中灰度共生矩阵(GLCM)占用空间大,以及计算量大、耗时的问题.该方法分三个步骤,首先,通过短时谱估计算法对鸟鸣声带噪功率谱进行音频增强;然后,采用和差统计法(SDH)对增强功率谱快速提取纹理特征;最后,由随机森林进行分类.在实验部分,设计了两组对比实验,结果表明,该方法有良好的识别性能、较少的时耗,且具有噪声鲁棒性.

关键词: 鸟鸣声识别, 抗噪纹理特征, 短时谱估计, 和差统计法

Abstract:

In order to improve the accuracy of bird sound recognition under non-stationary noise,a rapid bird sound recognition method using anti-noise texture features was proposed.This method also solved the problem of big occupation space,as well as large computation,time-consuming of gray level co-occurrence matrix (GLCM) in extracting texture features.The method contained three steps.Firstly,short-time spectrum estimation was conducted on noise spectrum of bird sound to get the enhanced spectrum.Then,sum and difference histograms (SDH) were applied to calculate texture features rapidly.Finally,random forest (RF) was used to make classification.In the experiment part,two contrast experiments were designed.The results show that this method has good recognition performance,lesser time consumption;meanwhile,it is robust to noise.

Key words: bird sound recognition, anti-noise texture features, short-time spectrum estimation, sum and difference histograms (SDH)

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