Different perceptual organization (PO) algorithms focus on different global cues

so people have to firstly judge the object's global cue from the image

and then apply the corresponding PO algorithm.This paper proposed a PO algorithm with global cue selection based on prior model to automatically select the global cue with biggest probability.The prior model firstly obtained the prior knowledge and the sample distribution respectively from the statistical quantity of specific field and the generalized Laplacian distribution

then expressed the importance of each kind of global cues as the normalized information which was calculated by the posterior probability and the cue probability.To accelerate the computation

the grouping seed ranking method was incorporated.Finally

application of the algorithm in coal-mine field is analyzed.The results show this algorithm is efficient.