The problem of histogram thresholding is tackled using a modular expert network. The modular expert network is a network of expert modules modulated by a gating network. The expert modules incorporate individual experts' opinions on the thresholding problem. The difficult task of integration of conflicting experts' opinions is achieved through a training of the gating network using backpropa- gation. The resulting network achieves accurate modeling of the solution mapping through the efficient combination of existing ex- perts. Experimental results show the superior performance of the modular network over classical algorithms. In particular, a near- optimal solution was shown to be achievable using a small training set. Application to a real-world biomedical cell segmentation prob- lem is also given. © 1997 SPIE and IS&T. (S1017-9909(97)00603-X)
['Chun Hung Li', 'Peter Kwong-Shun Tam']
Modular expert network approach to histogram thresholding