关键词: 活动轮廓, 符号压力函数, 水平集, 图像分割

Abstract: In order to solve the problems that geodesic active contour model and Chan-Vese（CV） model cannot segment the weak boundary and the gray uneven images at the same time, this paper presents an improved active contour model for image segmentation based on Double Signed Pressure Force functions（DSPF）. Firstly, a signed pressure force function is given based on image statistic information, which can segment the gray uneven images, and a weighted function of the global gray mean of the inside and the outside of contour curve is developed by combining the internal with the external gray mean values. Another signed pressure force function is defined by using image global information to segment the weak boundary images. Then, by combining the above two proposed signed pressure force functions, i.e. the signed pressure force function of statistic information and the other function of the global information（called as double signed pressure force functions）, a new evolution equation of level set is designed by adding the combined weighting coefficients. Finally, DSPF is introduced in the selective binary and Gaussian filtering regularized level set model, and a novel active contour image segmentation algorithm based on DSPF （DSPF-ACIS） is proposed. Experimental results show the advantages of the proposed method in segmenting the weak boundary and gray uneven images in terms of both efficiency and anti-noise performance.

Key words: active contour, signed pressure force function, level set;image segmentation