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Báo cáo hóa học: " Research Article Curvilinear Image Regions Detection: Applications to Mobile Robotics"

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: Research Article Curvilinear Image Regions Detection: Applications to Mobile Robotics | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2011 Article ID 145232 16 pages doi 10.1155 2011 145232 Research Article Curvilinear Image Regions Detection Applications to Mobile Robotics J. M. Perez-Lorenzo 1 A. Bandera 2 R. Marfil 2 and R. Vazquez-Martin3 1 Departamento deIngenieria Telecomunicación Universidad de Jaen 23700-Linares Spain 2 Grupo ISIS Departamento de Tecnologia Electrinica Universidad de Malaga 29071 Malaga Spain 3 Centro Andaluz Innovaciin y Tecnologia de Informaciin y Comunicaciones CITIC 29590-Malaga Spain Correspondence should be addressed to J. M. Perez-Lorenzo jmperez@ujaen.es Received 15 June 2010 Revised 25 August 2010 Accepted 19 October 2010 Academic Editor Yannis Kopsinis Copyright 2011 J. M. Perez-Lorenzo 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. This paper proposes a novel approach for visual features detection which is based on the presence of objects whose shape can be modelled using cylinders or generalized cylinders. These specific structures are commonly found on indoor and outdoor scenarios and their image representations the so-called curvilinear regions automatically deform with changing viewpoint as to keep on covering identical physical parts of a scene. The method is based on Marr s visual theory that proposes that visual objects can be decomposed in generalized cylinders. Also part of the method can be compared to the behavior of AOS neurons placed in the caudal intraparietal sulcus that respond when an elongated object is visualized. Our detector reliably finds the same curvilinear regions under different viewing conditions. Evaluation results are given to demonstrate the performance of the approach and its ability to be applied for visual features detection in a mobile robot navigation framework. 1. .