Statistical System of Cultural Heritage Tourism Information Based on Image Feature Extraction Technology

• Published in: Mathematical problems in engineering Vol. 2022; pp. 1 - 12
• Main Authors: Qin, Lulu, Chen, Shijun, Huang, Junpei, Lin, Han
• Format: Journal Article
• Language: English
• Published: New York Hindawi 19.07.2022; Hindawi Limited
• Subjects: Algorithms; Big Data; Cultural heritage; Cultural resources; Cultural tourism; Culture; Data analysis; Design; Feature extraction; Geographic information systems; Image classification; Information management; Internet; Object recognition; Optimization; Personal computers; Preprocessing; Software; Spatial analysis; Statistics; Technical services; Technology utilization; Tourism; Travel; Visualization
• ISSN: 1024-123X; 1563-5147
• DOI: 10.1155/2022/5250853

This paper presents an in-depth study of a statistical system using image feature extraction technology for cultural heritage tourism information. Based on the specificity of the tourism industry, it combines the technical architecture, framework of image feature extraction, GIS basic design, database design, and other related theories; realizes visual mapping through relevant tourism statistics in GIS; and uses the spatial analysis capability of ArcGIS software to complete the statistical scheme of cultural heritage tourism information data in the context of Internet big data. In this paper, the image preprocessing process is accelerated by the parallel optimization of the filtering operation and down-sampling operation in the relevant image preprocessing algorithm. The preprocessed images can effectively improve the recognition effect of the image feature extraction and classification stage. Based on cultural heritage tourism information mining results, the design and development of the tourism information statistics platform are carried out. The platform is built and developed using GIS secondary development technology and HTML + CSS front-end development technology API, Echarts, and other image feature components. The platform enables the massive and disorganized tourism text information to be displayed in a way that is easier to understand in both maps and text. This paper’s research on critical technologies provides technical support for image feature extraction of tourism statistics, which has specific practical value. Implementing the cultural heritage tourism platform offers a visual operating environment for tourism, enabling cultural heritage tourism businesses to tap into user preferences so that users can effectively access the travel options that interest them, which is conducive to promoting the development of travel recommendation platforms.