tailieunhanh - Báo cáo hóa học: " Research Article Robust and Accurate Curvature Estimation Using Adaptive Line Integrals"

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 Robust and Accurate Curvature Estimation Using Adaptive Line Integrals | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 240309 14 pages doi 2010 240309 Research Article Robust and Accurate Curvature Estimation Using Adaptive Line Integrals Wei-Yang Lin 1 Yen-Lin Chiu 2 Kerry R. Widder 3 Yu Hen Hu 3 and Nigel Boston3 1 Department ofCSIE National Chung Cheng University Min-Hsiung Chia-Yi 62102 Taiwan 2 Telecommunication Laboratories Chunghwa Telecom Co. Ltd. Yang-Mei Taoyuan 32601 Taiwan 3Department of ECE University of Wisconsin-Madison Madison WI53706 USA Correspondence should be addressed to Wei-Yang Lin wylin@ Received 18 May 2010 Accepted 4 August 2010 Academic Editor A. Enis Cetin Copyright 2010 Wei-Yang Lin 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 task of curvature estimation from discrete sampling points along a curve is investigated. A novel curvature estimation algorithm based on performing line integrals over an adaptive data window is proposed. The use of line integrals makes the proposed approach inherently robust to noise. Furthermore the accuracy of curvature estimation is significantly improved by using wild bootstrapping to adaptively adjusting the data window for line integral. Compared to existing approaches this new method promises enhanced performance in terms of both robustness and accuracy as well as low computation cost. A number of numerical examples using synthetic noisy and noiseless data clearly demonstrated the advantages of this proposed method over state-of-the-art curvature estimation algorithms. 1. Introduction Curvature is a widely used invariant feature in pattern classification and computer vision applications. Examples include contour matching contour segmentation image registration feature detection object recognition and so forth. Since curvature