基于生物声学信息的爬行动物和无尾动物自动识别方法

Juan J. Noda, David Sánchez-Rodríguez, C. Travieso-González
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引用次数: 2

摘要

如今,人类活动被认为是爬行动物和两栖动物生命的主要危险因素之一。这些生物的存在是良好环境质量的良好生物指标。由于它们的行为和大小,大多数这些物种在它们的生活环境中使用图像设备识别是复杂的。然而,在环境条件和能见度有限的大而偏远的地区,利用生物声学信息来识别动物物种是一种有效的方法来取样和控制这些生物的保护。在本章中,提出了一种基于Mel和线性频率倒谱系数(MFCC和LFCC)融合的爬行动物和无脊椎动物物种识别新方法。所提出的方法已在公共数据库中进行了验证,实验结果显示准确率在95%以上,表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Methodology Based on Bioacoustic Information for Automatic Identification of Reptiles and Anurans
Nowadays, human activity is considered one of the main risk factors for the life of reptiles and amphibians. The presence of these living beings represents a good biological indicator of an excellent environmental quality. Because of their behavior and size, most of these species are complicated to recognize in their living environment with image devices. Nevertheless, the use of bioacoustic information to identify animal species is an efficient way to sample populations and control the conservation of these living beings in large and remote areas where environmental conditions and visibility are limited. In this chapter, a novel methodology for the identification of different reptile and anuran species based on the fusion of Mel and Linear Frequency Cepstral Coefficients, MFCC and LFCC, is presented. The proposed methodology has been validated using public databases, and experimental results yielded an accuracy above 95% showing the efficiency of the proposal.
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