Affiliation:
1. School of Technology - University of Campinas, São Paulo, BR
Abstract
Point clouds resulting from digital scanning are increasingly being used in the heritage field to create knowledge-based models, such as
building information models (BIM)
. Nevertheless, the use of digital image processing techniques in point cloud unorganized data is not well explored yet because of the lack of information about point adjacency and corresponding difficulty in structuring and manipulating data. In this study we propose an approach to deal with image processing-like mathematical morphological operations in unorganized point cloud using the
octree
graph. Our method consists of three main steps, namely: (i) computing the best distance value between points in the cloud; (ii) constructing an
octree
from point cloud; and (iii) producing a graph using rectangular layout. We exemplify the use of the proposed methodology performing morphological operations in grayscale and color point clouds of historical buildings. Results prove the effectiveness of the
octree
representation, which can efficiently generate an adjacency map, demonstrated by the resulting images, and has the potential to be applied at different areas of 3D data analysis.
Funder
FAPESP São Paulo Research Foundation
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Graphics and Computer-Aided Design,Computer Science Applications,Information Systems,Conservation