Abstract: To solve the problem of optic disk detection being easily affected by light and weak contrast, a novel approach for automatic optic disk detection is proposed for effectively locating and segmenting the optic disk. First, preprocessing is applied to correct the uneven illumination and improve the low contrast. Then, a series of key points can be extracted using alternative sequential filters and regional maxima. Moreover, the key point that has the maximum correlation coefficient calculated by adaptive multi-scale template matching method is located as the center of the optic disc. Finally, the region of interest that contains the optic disc location is extracted, and the optic disc boundary can be effectively estimated using Canny edge detection and Hough transform technique. The proposed approach is tested on four publicly available databases, namely, DRIVE, DIRATEDB0, DIRATEDB1 and ROC. Experimental results show that the proposed approach performs better than state-of-the-art approaches.