RANDOM-SAMPLING THRESHOLDING - A NEW APPROACH TO MULTILEVEL THRESHOLDING

Abstract

In this paper, a new approach to multilevel thresholding is proposed. First, the approach uniformly spreads some coarse thresholds over the gray-level range. Then, an adjusting process is applied repeatedly until a certain stopping criterion is reached. In the process, some pixels are first randomly sampled. Then, those coarse thresholds are finely adjusted according to the distribution of their neighborhood in the histogram formed by the randomly sampled pixels. The proposed method can automatically determine the number of thresholds. Furthermore, if the number of the resulting thresholds is not sufficient under a certain sense, the proposed method can be iteratively applied, based on the previous results, to get more thresholds. Experimental results also show that the performance of the proposed method is comparable to that of the recent method presented by Lim.