Abstract: The classical edge-based level set segmentation models are not suitable for inhomogeneous region. To improve this, this paper analyzes the relationship between the sequential filtering and the number of the filter, combines the sequential filtering and the level set, finally, presents a new image segmentation model on the sequential filtering. To make the number of the smoothing depends on image data self-adaptively, this model segments the confidence of the region with smoothing components, designs the smoothing indicator, and controls the number of the sequential filtering. Let the contour curve with different smoothing components converge at the object boundary, effectively improve the results of the classical edge-based level set segmentation on inhomogeneous region. The F-measure, precision and recall of image segmentation in this model are all higher than the classical model, and the segmentation effect of inhomogeneous region is improved to some extent.
