Abstract:

Aiming at the problems of inaccurate segmentation and bad universality in traditional twodimensional (2-D) Otsu thresholding methods, a fast 2-D Otsu image thresholding method based on the second order generalized probability (SOGP) was proposed. First, a 2-D histogram was created with the improved neighborhood and the two-variable probability distribution of it was modified to the second order generalized probability to obtain better segmentation performance. Then, the values of objects area and background area in the 2-D histogram main-diagonal district in the Otsu method were precisely calculated to get a more accurate threshold, and the parameter of SOGP was selected to improve the method’s universality. Finally, a 2-D histogram was analyzed to get Otsu computing features, and a new recursive algorithm was inferred with the features to reduce the computational complexity. Experimental results showed that the proposed method could not only achieve more accurate segmentation results and more applicability, but also required much less memory space and running time, compared to the current 2-D Otsu thresholding methods.

Key words:  image segmentation, 2-D Otsu method, recursive algorithm, the second order generalized probability