Title :
Shape recognition from shadows of 3-D convex geometrical objects
Author :
Presles, B. ; Debayle, Johan ; Pinoli, J.
Author_Institution :
CIS-SPIN-LPMG, Ecole Nat. Super. des Mines de St.- Etienne, St. Étienne, France
fDate :
Sept. 30 2012-Oct. 3 2012
Abstract :
The aim of this article is to present a new projective stereological method which enables to estimate the size and the shape of a three-dimensional (3-D) convex geometrical object from measurements only made on some of its two-dimensional (2-D) projections. In order to do so, some geometrical and morphometrical measurements on the projected shadows of the 3-D convex object are done and the size and shape parameter values of the 3-D convex geometrical object are retrieved using the maximum likelihood estimation method. After several validation tests on synthetic 3-D convex objects, the proposed method is successfully applied to estimate the 3-D particle volume distribution during crystallization processes.
Keywords :
computational geometry; maximum likelihood estimation; shape recognition; stereo image processing; 2D projection; 3D convex geometrical object shadow; 3D particle volume distribution; crystallization process; geometrical measurement; maximum likelihood estimation; morphometrical measurement; projective stereological method; shape parameter value; shape recognition; Crystallization; Frequency modulation; Probability density function; Shape; Solid modeling; Vectors; Geometrical object analysis; Maximum likelihood estimation; Probability density function; Projective stereology; Shape diagrams;
Conference_Titel :
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4673-2534-9
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2012.6466908