Using homogeneous neighborhood in point clouds normal vector calculation

Point based 3D modeling has recently received greater attention، mainly due to its simplicity. One of the most fundamental operations for point set processing is to find the neighbors of each point in point clouds. This paper presents a new method called homogeneous neighborhood for determining neighbors in point clouds. This method of choosing neighbors، in addition to the distance takes into consideration the directional balance by improving the k nearest neighbors. The directional balance describes whether the neighbors are well spread around the point of concern. In this study effects of selecting neighbors on normal vector estimation are investigated. Normal vector is calculated using homogeneous neighborhood. For evaluation of the proposed method in determining neighbors، normal vector are calculated using the k nearest neighbors. The results show that the homogeneous neighborhood method is more accurate in normal vector estimation than the k nearest method. For evaluation of the homogeneous neighborhood method، it was employed in point cloud registration application. The results of registration by using the homogeneous neighborhood show that this method of neighbor selection yields reduced registration errors.