Vehicle Feature Extraction Method Based on Gammatone Filter Bank

A filter bank and feature extraction technology, applied in the field of pattern recognition, which can solve the problems of complex implementation, strong dependence on background noise, and large amount of calculation.

A filter bank and feature extraction technology, applied in the field of pattern recognition, which can solve the problems of complex implementation, strong dependence on background noise, and large amount of calculation.

CN103714810BActive Publication Date: 2016-05-25NORTHWEST INST OF NUCLEAR TECH
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  • Vehicle Feature Extraction Method Based on Gammatone Filter Bank
  • Vehicle Feature Extraction Method Based on Gammatone Filter Bank
  • Vehicle Feature Extraction Method Based on Gammatone Filter Bank

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Experimental program
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Embodiment Construction

[0058] The present invention applies the principle of frequency decomposition in auditory characteristics, and the process of extracting Gammatone cepstral coefficients from vehicle acoustic signals is as follows:

[0059] refer to figure 1 , the method of extracting vehicle acoustic signal features based on the Gammatone filter bank is:

[0060] 1) The sampling rate is f s (Satisfying the Nyquist sampling theorem, ie f s ≥2f max , f max is the highest frequency of the signal) the original vehicle acoustic signal s(n) is pre-filtered, normalized, and windowed and framed to obtain the short-term signal frame x(n) in the time domain. The corresponding calculations are as follows:

[0061] Signal low frequency enhancement: y(n)=s(n)+0.9375 s(n-1)(1)

[0062] Signal normalization: y ‾ ( n ) = y ( n ...

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Abstract

The invention discloses a vehicle model feature extraction method based on a Gammatone filter bank, belongs to the field of mode recognition, and relates to a method for feature extraction of a vehicle radiation sound signal, specifically to a method for feature extraction which simulates hearing characteristics of human ears by calculating a cepstrum coefficient of the vehicle sound signal under the Gammatone filter bank. The method can simulate the characteristic of nonlinear frequency resolution of human ears by using the Gammatone filter bank, and divides vehicle sound signal filtering into different sub-band signals and obtains a cepstrum coefficient. Based on the principle of frequency resolution in the hearing characteristics, the vehicle model feature extraction method based on the Grammatone filter bank extracts a Grammatone cepstrum coefficient from the vehicle sound signal, and obtains frequency band-energy features of an original signal, involved calculation concerns commonly-used signal processing techniques, the principle is simple, the steps are clear, programming realization is facilitated, and the applicability is wide.

Description

technical field [0001] The invention belongs to the field of pattern recognition, and relates to a feature extraction method of a vehicle radiated acoustic signal, specifically a feature extraction method for calculating the cepstral coefficient of a vehicle acoustic signal under a Gammatone filter bank, and the obtained features can simulate the hearing of the human ear characteristic. Background technique [0002] The process of car model recognition mainly includes two parts: feature extraction and classifier training and recognition. Feature extraction is one of the key technologies of pattern recognition, and using vehicle movement to generate acoustic signals to classify and recognize them is an important way for vehicle model recognition. Vehicle identification is widely used in areas such as traffic management, regional protection, and important areas of warning. [0003] At present, the feature extraction of vehicle acoustic signals is mainly based on the frequenc...

Claims

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Application Information

Patent Timeline
25 May 2016
Publication
CN103714810B
IPC
G10L15/02
Inventors
赵天青; 梁旭斌