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%.
Remote insurance mainly completes quotation, insurance application and payment through the PC terminal and mobile terminal, and the premium directly enters the insurance account. This article takes remote insurance as an example. First, it analyses the requirements of the remote insurance and insurance system, and then collects data from the mobile terminal. The system geographic information system (GIS) server subsystem and GIS information management subsystem are designed in three aspects. GPS data and video image data are collected and processed in the data acquisition subsystem, forwarded by the GIS server, and sent to the GIS information management subsystem. Geographic information system information management realises online loss determination through basic information query, geographic location identification, scheduling, path planning, real‐time tracking, image information etc. on the mobile terminal, combined with insurance and insurance business. In terms of implementation, the GIS information management platform and Google Maps are used to realise the monitoring, scheduling and path planning of the mobile terminal GIS online platform. And conduct experimental research on the content‐centric 5G structure. The results show that the transmission interference time of the content‐centric network‐based 5G structure is 390 ms, which is much lower than the 800 ms demanded for GSM‐R system. It proves that the content‐centric network‐based 5G structure has good mobile performance; the test of the content‐centric network verifies that the content‐centric network has the advantages of balancing network load and preventing network congestion; meanwhile, the test of the proposed The functions and performance of the GIS system proposed in this paper are tested. The results meet the user requirements.
The feature extraction of Gaofen-2 Remote Sensing Image (RSI) has problems such as poor extraction accuracy and large noise reduction error. Therefore, this paper designs an RSI feature extraction method based on high score 2 wavelet transform (WT). The RSI is collected with the help of Gaofen-2 satellite and high-resolution remote sensing technology, the key points of the image are determined through the Gaussian difference scale space, and the key points of the edge are judged by the peak curvature value of the difference function at the edge junction, so as to complete the RSI acquisition. Specific filtering and spatial domain transformations are used to remove image noise and improve the quality of RSI. The mean shift (MS) algorithm is used to iteratively find the area with the most dense sample points in the RSI space, complete the image analysis, and realize the preprocessing of the high score 2 RSI. The linear features of the RSI are determined by the WT algorithm, and the image threshold is set for feature extraction of the high score 2 RSI. The experimental results show that in the RSI noise reduction error analysis of different methods, the noise reduction error curve of the sample RSI of the method proposed in this paper has the lowest trend, which is always lower than 2%. Compared with the two methods proposed before, the error is higher. At the same time, in the accuracy analysis of key point feature extraction, the proposed scheme has better accuracy. Therefore, it can be seen that this method has better comprehensive performance, and the proposed method can effectively improve the feature extraction accuracy of RSI and reduce the noise in RSI.
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