Optimal multilevel thresholding based on molecular kinetic theory optimization algorithm and line intercept histogram

Abstract

Among all segmentation techniques, Otsu thresholding method is widely used. Line intercept histogram based Otsu thresholding method (LIH Otsu method) can be more resistant to Gaussian noise, highly efficient in computing time, and can be easily extended to multilevel thresholding. But when images contain salt-and-pepper noise, LIH Otsu method performs poorly. An improved LIH Otsu method (ILIH Otsu method) is presented, which can be more resistant to Gaussian noise and salt-and-pepper noise. Moreover, it can be easily extended to multilevel thresholding. In order to improve the efficiency, the optimization algorithm based on the kinetic-molecular theory (KMTOA) is used to determine the optimal thresholds. The experimental results show that ILIH Otsu method has stronger anti-noise ability than two-dimensional Otsu thresholding method (2-D Otsu method), LIH Otsu method, K-means clustering algorithm and fuzzy clustering algorithm.

Keywords

image segmentation / multilevel thresholding / Otsu thresholding method / kinetic-molecular theory (KMTOA) / line intercept histogram

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