基于车库电子地图的图像处理与矢量化存储研究
Research on Image Processing and Vectorization Storage Based on Garage Electronic Maps
AI总结：
本研究针对大型地下车库电子地图，提出了一种室内二维地图栅格数据的矢量化分类存储方法，利用网格索引法分类元素以实现高效存储与快速查询，并通过插值算法和导航测试验证了其准确性和可靠性。
摘要：
为了实现更精确的图像定义和数据分析，本研究对电子地图的矢量化和栅格化存储进行了研究，重点关注大型地下停车库地图。在研究过程中，进行了图像处理、矢量化和栅格化存储。本文提出了一种室内二维地图栅格数据的矢量化分类存储方法。该方法涉及将栅格数据转换为矢量数据，并利用网格索引法根据坐标位置对停车位、通道和障碍物等元素进行分类，从而促进室内地图的高效存储和快速查询。此外，采用插值算法提取矢量数据并将其转换为栅格数据。进行了导航测试以验证该方法下地图模型的准确性和可靠性，为车库地图的数字存储和导航提供了有效的技术支持。
英文摘要：
For the purpose of achieving a more precise definition and data analysis of images, this study conducted a research on vectorization and rasterization storage of electronic maps, focusing on a large underground parking garage map. During the research, image processing, vectorization and rasterization storage were performed. The paper proposed a method for the vectorization classification storage of indoor two-dimensional map raster data. This method involves converting raster data into vector data and classifying elements such as parking spaces, pathways, and obstacles based on their coordinate positions with the grid indexing method, thereby facilitating efficient storage and rapid querying of indoor maps. Additionally, interpolation algorithms were employed to extract vector data and convert it into raster data. Navigation testing was conducted to validate the accuracy and reliability of the map model under this method, providing effective technical support for the digital storage and navigation of garage maps.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
