Indexed in ISI - Awarded by Best Conference Paper Prize Abstract: - Digital applications such as CG, CAD and GIS are based on vectorial data since all the information about shape, size, topology etc. are provided in such kind of data representation rather than raster one. Turning raster images into vector ones is a key issue which has been addressed by a number of authors but still far to be exhaustively worked out. Especially in the case of 2D images representing technical drawings, fitting analytical curves to point clouds (pixel sets) is a critical matter. The present paper provides a novel approach to fit unordered point cloud data. Such an approach integrates a PCA-based method, for detecting the main local directions of the point cloud and to order the points, with and a weighted approximation of a B-spline curve to the original data, based on pixel gray levels. The methodology, tested against alternative techniques based on Least Square (LS) B-spline approximation and on image thinning, proved to be effective in preserving the original shape according to human perception.

From unordered point cloud to weighted B-Spline - a novel PCA-based method - / R.Furferi;L.Governi;M.Palai;Y.Volpe. - STAMPA. - Proceedings of: International Conference on COMPUTER ENGINEERING and APPLICATIONS (CEA '11):(2011), pp. 146-151. (Intervento presentato al convegno CEA '11 tenutosi a Puerto Morelos, Mexico nel January 29-31, 2011).

From unordered point cloud to weighted B-Spline - a novel PCA-based method -

FURFERI, ROCCO;GOVERNI, LAPO;PALAI, MATTEO;VOLPE, YARY
2011

Abstract

Indexed in ISI - Awarded by Best Conference Paper Prize Abstract: - Digital applications such as CG, CAD and GIS are based on vectorial data since all the information about shape, size, topology etc. are provided in such kind of data representation rather than raster one. Turning raster images into vector ones is a key issue which has been addressed by a number of authors but still far to be exhaustively worked out. Especially in the case of 2D images representing technical drawings, fitting analytical curves to point clouds (pixel sets) is a critical matter. The present paper provides a novel approach to fit unordered point cloud data. Such an approach integrates a PCA-based method, for detecting the main local directions of the point cloud and to order the points, with and a weighted approximation of a B-spline curve to the original data, based on pixel gray levels. The methodology, tested against alternative techniques based on Least Square (LS) B-spline approximation and on image thinning, proved to be effective in preserving the original shape according to human perception.
2011
Applications of Mathematics and Computer Engineering
CEA '11
Puerto Morelos, Mexico
January 29-31, 2011
R.Furferi;L.Governi;M.Palai;Y.Volpe
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/500656
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