Research on Image Processing and Vectorization Storage Based on Garage Electronic Maps
This work addresses digital storage and navigation for garage maps, but it appears incremental as it applies existing techniques like vectorization and rasterization to a specific domain.
The study tackled the problem of precise definition and data analysis for garage electronic maps by developing a vectorization classification storage method for indoor two-dimensional raster data, resulting in validated accuracy and reliability through navigation testing, though no concrete numbers were provided.
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.