Abstract: The optic disk localization is an important step before disk segmentation of fundus images. Since the optic disk localization can be easily influenced by the image contrast, we propose a fast optic disk localization method based on confidence score computation. Firstly, we perform morphological transformations to enhance the contrast between the optic disk and vessel regions from the background. According to the intensity features of pixels in the enhanced image, we localize the disk region roughly. Then, we apply the local sliding window scanning method to roughly localize the disk region and compute the confidence score of each candidate region based on the pixel intensity features in the window and the neighborhood vessel properties to generate the optic disk localization result. We conducted experiments on several publicly available datasets. The results show that the proposed method can successfully localize 1 325 optic regions among 1 341 images, and achieves 98.8% accuracy of the optic disk localization with each image consuming 0.25 s on average. The proposed method outperforms other existing optic disk localization methods and can be used in computer-aided eye disease diagnosis.