IMAGE SEGMENTATION WITH GVF FLOW AND DIRECTIONAL INFORMATION
Zhonghua Luo, Jitao Wu · International Journal of Wavelets Multiresolution and Information Processing · 2012
Intensity inhomogeneity is a common phenomenon in real-world images and may cause many difficulties in image segmentation. To overcome these difficulties, we propose a new active contour model combining the GVF flow and the directional information about edge location. On one hand, we incorporate the GVF flow into the proposed model to segment the images with intensity inhomogeneity efficiently. On the other hand, we construct an alignment term with the directional information to achieve sub-pixel accuracy and relax the placement of the initial curve. Moreover, a regularization term is also included in our model to ensure accurate computation and avoid time-consuming re-initializations. Experimental results on several synthetic and real images show that the proposed model is effective.