Ellipse extracting from weak edges based on GVF model and the least square method
基于改进GVF和最小二乘法的弱边界椭圆提取

A new fast approach which combines improved GVF model with least square method was proposed to extract ellipse by overcoming the influence of noise and weak edges. At first, the image was preprocessed through median filtering and gradient enhancing of weak boundary, and then the priori knowledge of target region intensity was employed to gain Gaussian fuzzy closeness, which combined with pressure force and formed fussy pressure force. Under the effect of GVF field and the new force, inner control points were pushed toward boundary rapidly, points on the boundary almost bore no forces and outer points bore strong repulsive forces which pushed the points back to the boundary. After iterating several times, the control points were fitted as ellipse by least square method, which was sampled to be new initial boundary of the improved GVF model. The shape-constrained curve deformable method was applied to footprint analysis system and extracted ellipse from blur, noise and weak boundary image precisely, while it was difficult for conventional edge detection methods. Simulation results show that the method is rapid and satisfying.