Fast thresholding for image segmentation based on 0-1 programming
Lu-Chen Chen · Computer Engineering and Applications Journal · 2012
The thresholding for image segmentation is an important and well-established method that has been widely applied to this problem. Conventional Otsu algorithm is however, computational suffering for using the exhaustive searching strategy to find the optimal thresholds. It is thus inapplicable in the selection of multilevel thresholds. In this paper, a modified Otsu method is proposed to determine the thresholds with improved efficiency. This is accomplished by transforming the Otsu method to a nonlinear 0-1 programming problem, which can be solved by genetic algorithms. The results on the testing images show that the computational speed of the proposed method is significantly improved to accommodate the general use of image segmentation.