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Objective  By using the characteristics of brightness and edge in hard exudates (HE), a new automatic HE detection method based on a Canny edge detection algorithm combined with morphological remodeling method is  proposed . The purposes are to solve problems like low sensitivity and interference of optic disk and vessels in other algorithms. It has great significance to the automatic screening of DR. Methods This algorithm could be divided into four steps. The first step was the image preprocessing, mainly including the selection of RGB channels and image contrast enhancement based on morphology. The second step was the elimination of key structures in retinal image. To avoid interference to the HE detection, the vessel segmentation method based on Gabor filter was used to eliminate the influence of blood vessel edge, and the proposed optic cup segmentation method was used in red channel to eliminate the optic disk and its edge. The third step was to extract the HE by using the improved Canny edge detection operator combined with morphological reconstruction method. The forth step was image post-prosessing based on morphology, eliminating the false positive area in image edges. At last ,we tested 40 images in the public database(35 images with HE lesions, 5 normal images). Results Its lesion based sensitivity and positive predictive value were 93.18%, 79.26%, respectively. Its image based sensitivity, specificity and accuracy were 97.14%, 80.00% and 95.00%, respectively. Conclusion  Comparing the above evaluation indexes with other methods, and the results proved the feasibility of the algorithm based on a Canny edge detection algorithm combined with morphological remodeling method.