Aiming at the problem of high error detection rate in complex background text location, a novel algorithm based on ant colony cluster algorithm is proposed for detecting and locating text regions in natural scene images. In the proposed method, firstly, statistical features of wavelet coefficients are used to represent text mode, and then ant colony cluster algorithm is selected to classify image pixels as text regions and background, thus all possible text regions are obtained. Secondly, Local Binary Pattern Histogram Fourier (LBP-HF) feature is applied to remove non-text areas which have the similar characteristics in wavelet domain. Experimental results demonstrate that verification procedure based on LBP-HF is effective, by which the error detection rate is reduced greatly for complex background text detection.