A Hybride Active Contour Model Driven by Global and Local Image Information

作者:Xu Li, Hairong Liu, Yu Xing

摘要

In this paper, a novel active contour model based on hybrid image fitting energy which utilizes both global and local image information is proposed. Two fitting images are constructed to approximate the original image and the square of the original image. Both global and local image information are incorporated into these two fitting images. Based on these two fitting images, a hybrid image fitting energy, which is then minimized in a variational level set framework to guide the evolving contours to the desired boundaries. The proposed approach is validated by experiments on both synthetic and real images. The experiments demonstrate that the proposed model is more efficient and robust for segmenting different kinds of images compared with several typical active contour models.

论文关键词:Image segmentation, Intensity inhomogeneity, Active contour, Level set, Hybrid model

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论文官网地址:https://doi.org/10.1007/s11063-019-10004-0