Rural Acoustic Landscape Analysis Based on Segmentation and Extraction of Spectral Image Feature Information

Abstract

Spectrogram is an image that can record voice information, which can be analyzed by analyzing the received image. Spectrograms are used in mechanical fault diagnosis systems to answer questions such as the location, type, and extent of the fault. It is the main tool for analyzing vibration parameters. In actual use, there are three types of spectrograms, namely linear amplitude spectrum, logarithmic amplitude spectrum, and self-power spectrum. The ordinate of the linear amplitude spectrum has a clear physical dimension and is the most commonly used. In this paper, the feature extraction information of rural acoustic landscape is mainly carried out through spectral images, which can effectively improve the segmentation efficiency, ensure the integrity of information, and determine the feasibility of establishing acoustic landscape in rural areas. This article aims to study the analysis of rural acoustic landscape in Guilin, Guangxi, based on the segmentation and extraction of spectral image feature information, through the segmentation and extraction of spectral image feature information, and then analyze the advantages and disadvantages of rural acoustic landscape. In this article, the Gabor wavelet filtering method is proposed to filter and analyze the spectral image. Through the detailed analysis of the insect and bird calls of the forest community near the village of Guilin, Guangxi, finally, the satisfaction and attention of the rural villagers to the acoustic landscape are investigated. The experimental results show that the sound of insects and birds reaches the maximum in spring and the minimum in autumn and winter. Moreover, the attention of rural villagers to acoustic landscape is also very high, with satisfaction of 87.12% and attention of 92.68%.