Illumination invariant active contour-based segmentation using complex-valued wavelets

This paper introduces a novel approach to the problem of active contour-based segmentation through the use of complex- valued wavelets. In traditional active contour-based segmentation techniques based on level set methods, the energy functionals are defined based on intensity gradients. This makes them highly sensitive to situations where the underlying image content is characterized by image non-homogeneities due to illumination and contrast conditions. In the proposed approach, the energy functionals used to evolve a level set function are based on the moments of phase coherence of complex-valued wavelet components. This formulation is highly invariant to non-homogeneities caused by illumination and contrast variations. Experimental results demonstrate that the proposed approach can be used to improve existing active contour-based segmentation methods under situations characterized by image non-homogeneities.