Fluorescence in situ hybridization (FISH) is a well-recognized technique for evaluating the human epidermal growth factor receptor 2 (HER2) gene status in breast cancer, where HER2 genes are seen as the red stained spots, and the chromosome centromere (CEN17) on which HER2 is located are visible as the green stained spots under a fluorescent microscope. The traditional manual analysis of FISH images is low efficient and has great subjective differences. Many researches focus on automatically calculating the average ratio of red/green spots in a cell and have achieved good performance. However, there are still a need to improve the segmentation accuracy of cells and HER2/CEN17 signals in FISH images with poor quality. In this paper, we propose a robust approach to locate HER2 and CEN17 signals based on the image standardization of varied FISH images. First we propose to use offset operation to reduce the fluorescence scattering, and to use exposure ratio map estimation and brightness transformation to enhance the weak fluorescence. Then we detect red/green spots by sequentially using top-hat filtering, thresholding and post-processing operations. The experimental results have shown that our proposed method can work well for the clinical FISH images with different quality.