Open AccessFast and robust ellipse detector based on edge following method
Author(s) -
Liu Yang,
Xie Zongwu,
Liu Hong
Publication year - 2019
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2018.5687
Subject(s) - ellipse , detector , curvature , enhanced data rates for gsm evolution , edge detection , convexity , computer science , artificial intelligence , least squares function approximation , computer vision , algorithm , line (geometry) , mathematics , geometry , image processing , image (mathematics) , statistics , telecommunications , estimator , financial economics , economics
This study presents a fast and robust ellipse detector based on edge following method. The detector first extracts segments using an edge predictor based on curvature analysis. Then, line segments are generated based on length condition other than least‐squares approximation. After that, potential ellipses are detected based on edge curvature and convexity. In addition, a re‐find contours detection method is introduced to improve the accuracy by searching edge points in the missing part of the ellipse. The performance of the detector has been tested on different datasets containing both synthetic and real images with three other algorithms based on the edge following method. Experimental results indicate that the proposed method always has the fastest execution time. Besides, it advances the state of the art in accuracy in most cases. Generally speaking, it is a fast, robust and effective ellipse detector for real‐time applications.