A hybrid framework for image segmentation

Huiyu Zhou, Tangwei Liu, Huosheng Hu, Yusheng Pang, Faquan Lin, Ji Wu

Abstract: This paper presents a new approach for image segmentation by combining the classical gradient vector flow (GVF) algorithm with mean shift. Due to the dependence on the gradient vectors of an edge map, the classical GVF is sensitive to the shape irregularities, and hence the snake cannot be ideally located on the concave boundaries. We propose an improved representation of the internal energy force by reducing the Euclidean distance between the guessed centroid and the estimated one of the snake. Experimental work shows the performance of this approach in different tests.