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: Evaluating Edge Detection through Boundary Detection | Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006 Article ID 76278 Pages 1-15 DOI ASP 2006 76278 Evaluating Edge Detection through Boundary Detection Song Wang Feng Ge and Tiecheng Liu Department of Computer Science and Engineering University of South Carolina Columbia SC 29208 USA Received 27 February 2005 Revised 6 June 2005 Accepted 30 June 2005 Edge detection has been widely used in computer vision and image processing. However the performance evaluation of the edgedetection results is still a challenging problem. A major dilemma in edge-detection evaluation is the difficulty to balance the objectivity and generality a general-purpose edge-detection evaluation independent of specific applications is usually not well defined while an evaluation on a specific application has weak generality. Aiming at addressing this dilemma this paper presents new evaluation methodology and a framework in which edge detection is evaluated through boundary detection that is the likelihood of retrieving the full object boundaries from this edge-detection output. Such a likelihood we believe reflects the performance of edge detection in many applications since boundary detection is the direct and natural goal of edge detection. In this framework we use the newly developed ratio-contour algorithm to group the detected edges into closed boundaries. We also collect a large data set 1030 of real images with unambiguous ground-truth boundaries for evaluation. Five edge detectors Sobel LoG Canny Rothwell and Edison are evaluated in this paper and we find that the current edge-detection performance still has scope for improvement by choosing appropriate detectors and detector parameters. Copyright 2006 Hindawi Publishing Corporation. All rights reserved. 1. INTRODUCTION Edge detection is a very important feature-extraction method that has been widely used in many computer vision and image processing applications. The basic idea of most .
