Multi-modal ray-level histogram modeling and decomposition

摘要

in this paper. We present a novel multi-modal histogram thresholding method in which no a priori knowledge about the number of clusters to be extracted is needed. The proposed method combines regularization an statistical approaches. By converting the approaching histogram thresholding problem to the mixture Gaussian density modeling problem, threshold values can be estimated precisely according to the parameters belonging to each contiguous cluster. Computational complexity has been greatly reduced since our method does not employ conventional iterative parameter refinement. Instead, an optimal parameters estimation interval was defined before the estimation procedure.