图像分割中局部能量驱动的快速主动轮廓模型

为了解决图像对象灰度分布不一致性的分割难题,提高图像分割速度,提出了一个全新的快速主动轮廓模型。它由曲线周围局部的统计信息驱动曲线发生形变演化,并使用图像中的边缘信息来引导曲线的演化方向。模型中,根据区域模板与演化曲线共同定义的局部统计信息创建数据拟合项,并应用水平集方法求解曲线的演化。对合成图像和医学图像的实验结果表明,本文提出的分割模型可以同时分割多个灰度不一致的对象,分割速度快,结果稳定,对噪声具有很好的鲁棒性。

A fast active contour model for image segmentanon driven by local region energy

In order to overcome the difficulties caused by intensities in-homogeneity and improve the speed of image segmentation,we propose a novel active contour model in which the curve evolution is driven by the statistical information around the curve,and the curve is forced to march toward the boundary under the alignment term.In our model,the data fitting term,which is constructed by the local information between the curve and mask,is incorporated into a variational level set formulation to be solved.Experiment...