tailieunhanh - Báo cáo sinh học: " Research Article Error Evaluation in a Stereovision-Based 3D Reconstruction System"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: Research Article Error Evaluation in a Stereovision-Based 3D Reconstruction System | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2010 Article ID 539836 12 pages doi 2010 539836 Research Article Error Evaluation in a Stereovision-Based 3D Reconstruction System Abdelkrim Belhaoua 1 Sophie Kohler 2 and Ernest Hirsch1 1LSIIT UMR CNRS-UdS 7005 Université de Strasbourg Bd Sébastien Brant BP 10413 67412 Illkirch Cedex France 2MIPS EA 2332 Université Haute Alsace 12 rue des freres Lumiere 68093 Mulhouse Cedex France Correspondence should be addressed to Sophie Kohler Received 1 December 2009 Revised 21 May 2010 Accepted 29 June 2010 Academic Editor Pascal Frossard Copyright 2010 Abdelkrim Belhaoua et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. The work presented in this paper deals with the performance analysis of the whole 3D reconstruction process of imaged objects specifically of the set of geometric primitives describing their outline and extracted from a pair of images knowing their associated camera models. The proposed analysis focuses on error estimation for the edge detection process the starting step for the whole reconstruction procedure. The fitting parameters describing the geometric features composing the workpiece to be evaluated are used as quality measures to determine error bounds and finally to estimate the edge detection errors. These error estimates are then propagated up to the final 3D reconstruction step. The suggested error analysis procedure for stereovision-based reconstruction tasks further allows evaluating the quality of the 3D reconstruction. The resulting final error estimates enable lastly to state if the reconstruction results fulfill a priori defined criteria for example fulfill dimensional constraints including tolerance information for vision-based quality control applications for .