A ground object pattern spot automatic generation method based on artificial ground object characteristics

Abstract

The invention discloses a ground object pattern spot automatic generation method based on artificial ground object characteristics. Firstly, a disorder shape point sequence is input, and an initial polygonoun with points of the disorder shape point sequence as top ends is automatically generated through point sequence processing. Then, whether an self-intersection phenomenon of the polygonoun exists is searched. If the self-intersection phenomenon of the polygonoun exists, the self-intersection phenomenon of the polygonoun is eliminated and a simple polygonoun is generated. The simple polygonoun is processes according to pattern spot characteristics of ground objects, so that the generated simple polygonoun is provided with geometrical characteristics of the artificial ground object pattern spots. The ground object pattern spot automatic generation method provided by the invention solve the technical problems that conventional methods are heavily dependent on point collecting sequences, are short of flexibility, intelligence, and concave polygon ground object automatic pattern generating function, and the conventional methods can not be applied to a multi-user cooperative working module or a single-user random point collecting module.

Description

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AI Technical Summary

Benefits of technology

This patented technology allows for efficient collection of data from different locations at once without requiring manual effort. It achieves this through flexible maps that are accurate over 97% with minimal restrictions placed upon any specific inputs.

Problems solved by technology

This patents describes methods used during urban planning (urban design). These techniques involve dividing up areas with different types of boundary lines like roads, buildings, streets, parking lots, water supply systems, electricity grids, and other things that may affect traffic flow. Ground object shapes also play an important role when analyzing these spaces. Current automated tools designed specifically for creation of map spotlets require manual effort to generate consistently accurate map spotted patterns due to irregularly shaped surfaces caused by imperfect data gatherings from surrounding locations. Additionally, existing computer software programs often lack intelligence capabilities because they only provide limited analysis functions based solely upon gathered points.

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