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Building an accurate 3D model of a circular feature for robot vision

Li L.

Opto-Electronics Review

2012

Vol. 20, No. 2

120-125

In this paper, an accurate 3D model analysis of a circular feature is built with error compensation for robot vision. We propose an efficient method of fitting ellipses to data points by minimizing the algebraic distance subject to the constraint that a conic should be an ellipse and solving the ellipse parameters through a direct ellipse fitting method by analysing the 3D geometrical representation in a perspective projection scheme, the 3D position of a circular feature with known radius can be obtained. A set of identical circles, machined on a calibration board whose centres were known, was calibrated with a camera and did the model analysis that our method developed. Experimental results show that our method is more accurate than other methods.

A randomized algorithm for detecting multiple ellipses based on least square approach

Li L., Feng Z., He K.

Opto-Electronics Review

2005

Vol. 13, No. 1

61--67

In this paper, a randomized method for detecting multiple ellipses based on the least square approach is presented. The main concept used is that we first randomly select three edge pixels in the image, which are the centre of three windows with the same size. In order to determine a possible ellipse, we use the least square method to fit all the edge points in these three window, and to solve the ellipse parameters through Lagrange multiplier method. Then we randomly select the fourth edge pixel in the image and define a distance criterion to determine whether there is a possible ellipse in the image. After finding a possible ellipse, we apply a further verification process to determine whether the possible ellipse is a true ellipse or not. Some artificial images with different levels of noises and some natural grey images containing circular objects with some occluded ellipses and missing edges have been taken to test the performance. Experimental results demonstrate that the proposed algorithm is faster and more accurate than other methods.