Point cloud pre-processing and surface reconstruction based on chord algorithm technique

Abstract EN

3D laser scanner is one of the modern technologies, which used to obtain the geometric information about the 3D scanned object surface.

But, there are some problems that are associated with this technique such as the huge number of obtained points which require high memory to save and the required data processing processes.

This paper proposed a data simplification algorithm for point cloud of a scanned object using 3D laser scanner (Matter and Form) in a manner to extract the necessary geometric features, which are represented by points for a 3D object.

This algorithm based on the instantaneous calculation of chord height of each set of adjacent points in the point cloud.

A MATLAB environment was used to build a proposed simplification algorithm program.

Then this program was applied using a proposed case study.

The result which was obtained from the application of the proposed algorithm and surface fitting process for the proposed case study proved the effectiveness of the proposed algorithm in data simplification.

The percent of data which was ignored as noisy data point was (24%) of the total number of data point in applying the algorithm for two attempts.