tailieunhanh - Báo cáo hóa học: "Design of Experiments for Performance Evaluation and Parameter Tuning of a Road Image Processing Chain"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Design of Experiments for Performance Evaluation and Parameter Tuning of a Road Image Processing Chain | Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006 Article ID 48012 Pages 1-10 DOI ASP 2006 48012 Design of Experiments for Performance Evaluation and Parameter Tuning of a Road Image Processing Chain Yves Lucas 1 Antonio Domingues 2 Driss Driouchi 3 and Sylvie Treuillet4 1 Laboratoire Vision et Robotique IUT Mesures Physiques Universite d Orleans 63 avenue de Lattre 18020 Bourges cedex France 2 Laboratoire Vision et Robotique ENSIB 10 Bd Lahitolle 18000 Bourges France 3 Laboratoire de Statistiques Theoriques et Appliquees Universite Pierre Marie Curie 175 rue du Chevaleret 75013 Paris France 4 Laboratoire Vision et Robotique Polytech Orleans 12 rue de Blois BP 6744 45067 Orleans France Received 1 March 2005 Revised 20 November 2005 Accepted 28 November 2005 Tuning a complete image processing chain IPC is not a straightforward task. The first problem to overcome is the evaluation of the whole process. Until now researchers have focused on the evaluation of single algorithms based on a small number of test images and ad hoc tuning independent of input data. In this paper we explain how the design of experiments applied on a large image database enables statistical modeling for IPC significant parameter identification. The second problem is then considered how can we find the relevant tuning and continuously adapt image processing to input data After the tuning of the IPC on a typical subset of the image database using numerical optimization we develop an adaptive IPC based on a neural network working on input image descriptors. By testing this approach on an IPC dedicated-to-road obstacle detection we demonstrate that this experimental methodology and software architecture can ensure continuous efficiency. The reason is simple the IPC is globally optimized from a large number of real images and with adaptive processing of input data. Copyright 2006 Hindawi Publishing Corporation. All rights reserved. 1. ADAPTIVE .