tailieunhanh - Báo cáo hóa học: " A Method for Assessment of Segmentation Success Considering Uncertainty in the Edge Positions"

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: A Method for Assessment of Segmentation Success Considering Uncertainty in the Edge Positions | Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006 Article ID 21746 Pages 1-12 DOI ASP 2006 21746 A Method for Assessment of Segmentation Success Considering Uncertainty in the Edge Positions Ruben Usamentiaga Daniel F. García Carlos Lopez and Diego Gonzalez Department of Computer Science University of Oviedo Campus de Viesques 33204 Gijon Asturias Spain Received 27 February 2005 Revised 6 June 2005 Accepted 27 June 2005 A method for segmentation assessment is proposed. The technique is based on a comparison of the segmentation produced by an algorithm with an ideal segmentation. The procedure to obtain the ideal segmentation is described in detail. Uncertainty regarding the edge positions is accounted for in the discrepancy calculation of each edge using fuzzy reasoning. The uncertainty measurement consists of a generalization using fuzzy membership functions of the similarity metrics used by well-known assessment methods. Several alternatives for the fuzzy membership functions based on statistical properties of the possible positions of each edge are defined. The proposed uncertainty measurement can be easily applied to other well-known methods. Finally the segmentation assessment method is used to determine the best segmentation algorithm for thermographic images and also to tune the optimum parameters of each algorithm. Copyright 2006 Ruben Usamentiaga 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. 1. INTRODUCTION Image segmentation is one of the most important components in an image analysis system. The objective of segmentation is to divide the image into meaningful regions. After the segmentation features of each region are identified to be used for further analysis. Since the analysis of the image is based on the identified features and the .

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