南京大学学报(自然科学版) ›› 2015, Vol. 51 ›› Issue (7): 16–.

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基于时频图像处理的宽吻海豚声通讯信号自动检测方法

孙馨喆1,2,文立1,2,杨武夷1,2*,张宇1,2   

  • 出版日期:2015-12-26 发布日期:2015-12-26
  • 作者简介:(1.厦门大学水声通信与海洋信息技术教育部重点实验室,厦门,361000; 2. 厦门大学海洋与地球学院,厦门,361000)
  • 基金资助:

    收稿日期: 2015-06-30

    * 通讯联系人, E-mail: wyyang@xmu.edu.cn

Detection method for whistles of bottlenose dolphin (tursiops truncatus) based on spectrogram processing

Sun Xinzhe1,2, Wen li1,2, Yang Wuyi1,2*, Zhang Yu1,2   

  • Online:2015-12-26 Published:2015-12-26
  • About author: (1. Key Laboratory of Underwater Acoustic Communication and Marine Information Technology Ministry of Education, Xiamen University, Xiamen, 361005, China;2. College of Ocean and Earch Sciences, Xiamen University, Xiamen, 361005, China)

摘要: 人工检测宽吻海豚声通讯信号效率低下。本文提出了一种基于信号时频图像处理的方法,旨在实现对宽吻海豚声通讯信号的高效自动检测。该方法首先对采集到的音频信号进行分帧,计算每帧信号的时频图;对时频图进行中值滤波后利用自适应局部阈值法提取时频图中通讯信号的轮廓;对提取的轮廓进行连通域分析,根据各连通域的能量和持续时间过滤噪声连通域;合并邻近的连通域后根据连通域的位置判断海豚通讯信号在音频信号中的起止时刻。实验结果显示本文的检测方法准确率达到了95%,该方法为海豚声信号的自动观测及其生物学行为的研究提供了一定的技术基础。

Abstract: It is inefficient to detect whistles of bottlenose dolphin artificially. This study proposes an automatic method to efficiently detect whistles, which is based on processing the spectrogram of signal. Audio signal is firstly segmented into frames. After median filtering of the spectrogram of each frame, adaptive thresholding method is used to detect whistle contours in the spectrogram. Connected components are extracted to identify the whistle contours. According to the energy and duration of a connected component, noisy connected components are removed. Adjacent connected components are merged. The locations of connected components are used to judge the whistles’ positions in the audio signal. Experimental results show that the accuracy of the proposed method is above 95%. The method can provide technical support for acoustic study of dolphins’ biological behavior.

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