The cross entropy in the existing thresholding methods does not satisfy the symmetricity of distance measure. And the computation speed of the algorithms can be further improved. Thus an image threshold selection method based on decomposition and two dimensional symmetric cross entropy is proposed in this paper. Firstly

the difference between the segmented image and the original one is measured by the symmetric cross entropy. The threshold selection formulae are derived based on the one dimensional and two dimensional symmetric cross entropy

respectively. A two dimensional fast recursive algorithm is given

which makes the computation complexity reduced to O(L2) from O(L4) of full search. Then the computation of two dimensional symmetric cross entropy is converted into two one dimensional spaces and its computation complexity is further reduced to O(L). The experimental results show that

compared with the existing threshold selection method based on two dimensional nonsymmetric cross entropy

the proposed method has stronger anti noise and the processing time is significantly reduced. It is an effective threshold selection method based on two dimensional cross entropy.