Point Cloud Pre-Processing and Surface Reconstruction Based on Chord Algorithm Technique
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.
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