System and method for mobile 3D scanning and measurement

A computer-implemented method of three-dimensional scanning and measurement, comprising:

• scanning, by a mobile device, a plurality of images of an object;
• receiving, by a processor, the plurality of images;
• preprocessing, by the processor, each of the plurality of images using morphological refinement;
• creating, by the processor, a plurality of point clouds from the preprocessed plurality of images;
• determining, by the processor and for each point cloud, prominent features by:
• estimating, by the processor, a curvature of each of the plurality of point clouds;
• and thereafter
• refining, by the processor, the estimated curvature by iteratively calculating the curvature over one or more iterations, such that a region of high curvature is re-calculated by a consideration of a smaller neighborhood in the region;
• and
• repeating, by the processor, the iterations until sampling in the smaller neighborhood does not increase the curvature in the region by more than a specified threshold;
• ranking, by the processor, the prominent features in each point cloud the based on the curvature determined therefor, matching, by the processor, points with similar curvature based on the curvature determined therefor;
• generating, by the processor, a transformed point cloud based on the prominent features in each point cloud of the plurality of point clouds;
• and
• determining, by a trained model, an overlap between the plurality of point clouds and labeled correspondences between prominent features thereof.

A non-transitory computer-readable medium having stored thereon computer- executable instructions that, when executed by a system to scan and measure three-dimensional features, the instructions comprising instructions to:

• receive a plurality of images of an object;
• preprocess each of the plurality of images using morphological refinement;
• create a plurality of point clouds from the preprocessed plurality of images;
• determine, for each point cloud, prominent features by a determination of:
• an estimate of a curvature of each of the plurality of point clouds;
• and thereafter
• a refinement of the estimated curvature by an iterative calculation of the curvature over one or more iterations, such that a region of high curvature is re-calculated by a consideration of a smaller neighborhood in the region;
• and
• a repetition of the iterations until a sample of the smaller neighborhood does not increase the curvature in the region by more than a specified threshold;
• rank the prominent features in each point cloud the based on the curvature determined therefor;
• match points with similar curvature based on the curvature determined therefor;
• generate a transformed point cloud based on the prominent features in each point cloud of the plurality of point clouds;
• and
• determine an overlap between the plurality of point clouds and labeled correspondences between prominent features thereof.