Đang chuẩn bị liên kết để tải về tài liệu:
Báo cáo hóa học: "Research Article An Image Content Description Technique for the Inspection of Specular Object"

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 An Image Content Description Technique for the Inspection of Specular Object | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 195263 14 pages doi 10.1155 2008 195263 Research Article An Image Content Description Technique for the Inspection of Specular Objects Y. Caulier1 and S. Bourennane2 1 Image Processing and Medical Engineering Department Fraunhofer Institute 91058 Erlangen Germany 2 Multidimensional Signal Group Fresnel Institute Ecole Centrale Marseille 13451 Marseille Cedex20 France Correspondence should be addressed to Y. Caulier cau@iis.fraunhofer.de Received 8 May 2008 Accepted 31 July 2008 Recommended by Satya Dharanipragada This paper proposed an image content description method within the context of specular surface inspection. Such a method is based on a preliminary research concerning the generation of specific stripe patterns for the visual enhancement of defective surface parts of cylindrical specular objects. The goal of this paper is to address the stripe pattern interpretation within a general approach. For this purpose different pattern recognition processes consisting not only of the combination of different image segmentation feature retrieval and classification but also of feature combination and selection will be considered. Three top-down and one bottom-up approaches are evaluated for retrieving the most appropriate feature sets in terms of highest classification rates. It will be demonstrated that following a combination and appropriate selection of these feature sets even better rates can be reached. With only half of the initial features an increase of more than 2 is observable. Copyright 2008 Y. Caulier and S. Bourennane. 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. 1. INTRODUCTION A major challenge of a typical machine vision process is to provide a rugged and cost-effective solution for .