Detection of Partial Ellipses Using Seperate Parameters Estimation Techniques
Wei Wen, Baozong Yuan · 1994
Ellipses are a powerful feature and are useful in computer vision. Most techniques pr ellipse fitting can be divided into two main classifications: one is the least square estimation (LSE) method and the other is the Hough transform (HT). They either make certain assumptions about the type of noise distribution, or require input parameters. This often prevents the techniques working robustly over a large range of data. A simple algorithm for partial ellipse detection using seperate parameters estimation techniques is proposed. The new method consists of two steps: (1) detect the elliptical center using its skewed symmetry properties; (2) estimate the other three parameters (A. B, 6) using the median of the intercepts (MI). The new method has been tested on both the synthetic and real images. The experimental results show that the method is reliable and accurate.