In the study of text detection, the proposal extraction method is not widely concerned and deeply studied, due to the structure of the text and otherness of the general object and the high precision requirement of text detection. In this paper, we propose a proposal extraction method for text detection. The proposed method firstly utilize the fully convolutional network to predict the text regions, which can effectively reduce the search range of the proposal extraction. Then, the EdgeBox algorithm is improved to make it suitable for the text proposal extraction in natural scenes. In addition, the proposed method is evaluated on two standard natural scene text detection benchmarks, and compared with other existing methods. Results show that the proposed method has better performance and robustness than other methods.