The max-flow model is used as a powerful tool to image segmentation problems. In recent years

a new model based on the continuous max-flow approach is presented and well adapted to segment images. However

the constraint of spatial flow in the model is simply set to a global constant

and it is not associated with architectural feature. Meanwhile

the initial terms of the source flow and sink flow need large amount of calculation

and cannot obtain satisfactory segmentation results. In order to overcome these shortages

we combine architectural features and statistical features of the image and a preprocessing algorithm

which include piecewise constant algorithm and Otsu-Histogram algorithm. Experimental results verify that the model is efficient.