Research on Image Processing and Vectorization Storage Based on Garage Electronic Maps

Fuente: arXiv
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Auteurs principaux: Dou, Nan, Shi, Qi, Lian, Zhigang
Format: Preprint
Publié: 2024
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author Dou, Nan
Shi, Qi
Lian, Zhigang
author_facet Dou, Nan
Shi, Qi
Lian, Zhigang
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2406_18567
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Research on Image Processing and Vectorization Storage Based on Garage Electronic Maps
Dou, Nan
Shi, Qi
Lian, Zhigang
Computer Vision and Pattern Recognition
Databases
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.
title Research on Image Processing and Vectorization Storage Based on Garage Electronic Maps
topic Computer Vision and Pattern Recognition
Databases
url https://arxiv.org/abs/2406.18567