Progressive Dynamic Registration Method for Tile Maps Based on Optimum Multi-Features
Source abstract
Abstract
Different tile maps may use different coordinate systems, and it is difficult to superimpose maps from different sources. In this regard, we propose a progressive dynamic registration (PDR) method based on optimum features extracted from images of tile map screenshots of a certain scale. Using this method, we can automatically register maps in roughly the same area from different sources without knowing the map project information. The better features among feature points and feature surfaces are selected for image registration based on the richness of the features in the map, and a new matching filter that combines the characteristics of the tile map and the features is proposed. In the progressive registration process during map zooming, the result of the adjacent scales are used as reference values for coarse registration. After experimental verification in different areas, the root mean square error of PDR is below 2.5 in different maps and is better than that of the registration method using feature points only. Moreover, the registration accuracies of remote sensing maps in all areas and vector maps in nonurban areas are better than that of the method based on coordinate system transformation. The calculation results of PDR can register not only the tile maps but also other nontiled vector or remote sensing data.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Robotics and Sensor-Based Localization · Advanced Image and Video Retrieval Techniques · Image Retrieval and Classification Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
Funding
National Natural Science Foundation of China
References (32)
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