Nipponia nippon individual recognition method based on MFCC algorithm

An identification method, the crested ibis technology, applied in the field of individual identification, can solve problems not related to the individual identification of crested ibis

Inactive Publication Date: 2014-10-15
XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY
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Problems solved by technology

[0004] In the prior art, researches have been conducted on the song characteristics of the crested ibise and the relationship between the song characteristics and behavior, but none of them involve the identification of crested ibis individuals

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  • Nipponia nippon individual recognition method based on MFCC algorithm
  • Nipponia nippon individual recognition method based on MFCC algorithm
  • Nipponia nippon individual recognition method based on MFCC algorithm

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Embodiment Construction

[0087] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0088] Such as figure 1 Shown is a block diagram of a method for individual recognition based on the song of the crested ibis in the present invention. The specific steps of the individual recognition method based on the crested ibis song are as follows:

[0089] 1. Preprocessing of the sound signal

[0090] (1) Pre-emphasize the collected song signal of a single crested ibis

[0091] Since the average power of the sound signal will be affected by the glottal excitation, the high-frequency part begins to attenuate greatly above about 800 Hz. When calculating the voice spectrum, the components of the high-frequency part are smaller, which is more difficult to find than the spectrum of the low-frequency part. The upper and lower frequencies are mixed with 50Hz or 60Hz interference information, so pre-emphasis is required. The purpose is to e...

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Abstract

The invention discloses a nipponia nippon individual recognition method based on an MFCC (Mel Frequency Cepstrum Coefficient) algorithm. The method comprises the following steps that: (1) collected nipponia nippon warbling signals are subjected to preprocessing including pre-emphasis, framing and windowing, and end point detection; (2) through fast Fourier transform, a power spectrum of the nipponia nippon warbling signals is obtained, and after the power spectrum is smoothened, a measure of combining the MFCC, a Mid MFCC and an IMFCC (Inverse Mel Frequency Cepstrum Coefficient) is used for extracting feature parameters; and (3) an improved wavelet neural network is utilized for carrying out training recognition on the feature parameters of the nipponia nippon warbling signals. The nipponia nippon individual recognition method has good anti-noise performance, the feature parameters which can better express the nipponia nippon warbling features can be extracted out, and the recognition rate of a system can be improved.

Description

【Technical field】 [0001] The invention belongs to the technical field of signal processing, in particular to an individual identification method. 【Background technique】 [0002] The crested ibis is an endangered bird in the world today (IUCN endangered level: endangered, 1996), and it is a first-level key protected animal in my country. [1] . Historically, it was widely distributed in my country, Japan, the Korean Peninsula and the Far East of Russia. Since the 1950s, due to environmental degradation and human hunting, the number of crested ibises has decreased sharply. The Korean Peninsula and other places became extinct one after another, and there was no record of crested ibis in my country for more than 20 years. Since 7 wild crested ibises were rediscovered in Yang County in 1981, the Chinese government has taken strong protection measures and established a national crested ibises nature reserve. Bird song plays an important role in promoting the evolution of birds, a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G10L17/26
Inventor 王民张立材王佳丽王稚慧张炜炜卫名斐曹清菁要趁红赵伟
Owner XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY
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