Abstract
To improve the accuracy of the aircraft cabin decoration style recommendation algorithm, an aircraft cabin decoration style recommendation algorithm based on machine vision is proposed. The outline diagram of aircraft cabin decoration style is described with the help of hog features, and the clustering observation is carried out through K-means clustering algorithm to complete the feature description of aircraft cabin decoration style. The background pixels of aircraft cabin decoration are determined with the help of Gaussian mixture model method, the style feature points to be measured are updated gradient, the input aircraft cabin decoration style sequence image is compared with the background image, the difference of statistical information such as gray characteristics of pixels or straight image is analyzed, and the background preprocessing of aircraft cabin decoration style is completed. This study analyzes the basic principle and operation process of machine vision system, obtains the aircraft cabin decoration style image with the help of machine vision, calculates the weight value of recommended users, determines the number of decoration style recommendations, and completes the aircraft cabin decoration style recommendation. The experimental results show that the proposed method can effectively improve the accuracy of aircraft cabin decoration style recommendations, and it is feasible.
Highlights
With the vigorous development of civil aviation in today’s society, more and more people have begun to choose to travel by air
In order to make up for the shortcomings of the above methods, an aircraft cabin decoration style recommendation algorithm based on machine vision is proposed in this study
(3) e experimental results show that the proposed method can effectively improve the accuracy of aircraft cabin decoration style recommendation, and it is feasible
Summary
With the vigorous development of civil aviation in today’s society, more and more people have begun to choose to travel by air. In order to make up for the shortcomings of the above methods, an aircraft cabin decoration style recommendation algorithm based on machine vision is proposed in this study. In the background of aircraft cabin decoration style, for the pixels to be measured, the Gaussian mixture model is processed by gradient updating [13] with the help of EM algorithm, and the following results are obtained: bm←bm + θ cm − bm,. Θ represents the learning rate and xnt represents the dependent parameters On this basis, the input aircraft cabin decoration style sequence image is compared with the background image, the difference of statistical information such as gray characteristics of pixels or straight images is analyzed, the abnormal situation is judged, and the moving target is detected and recognized.
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