IEEE International Conference on Image Processing (Brussel, 2011.)

Parametric active contours are efficient tools for boundary detection. However, existing external-energy-inspired methods have difficulties when detecting high curvature, noisy or low contrasted contours and they often suffer from initialization sensitivity.

To address these issues, the Distributed Events Analysis Research Laboratory 's work introduces Harris-based Vector Field Convolution (HVFC), operating with the modified characteristic function of Harris corner detector used in the feature map of the external force component of the Vector Field Convolution (VFC) state-of-the-art method. The automatic initial contour is calculated as the convex hull of the most salient points of the map. Experimental results show that HVFC outperforms other state-of-the-art methods, when tested on high curvature, noisy or low-contrasted contours.