This study aims to explore the role of melatonin in the regulation of retinal light sensitivity using computer vision technology. By performing edge detection on the fundus images from the E-Ophtha, Retinal Disease Classification, and Fundus Image Registration (FIRE) datasets, we successfully extracted the blood vessel edges using algorithms such as Canny edge detection, Sobel operator, and Prewitt operator. The results indicate that while the performance of edge detection algorithms varies across different datasets, they are generally effective in extracting the blood vessel structures in fundus images. Furthermore, we simulated the processing of fundus images under different lighting conditions to verify the role of melatonin in the regulation of retinal light sensitivity. By brightening and dimming the images, we found that changes in melatonin levels significantly affect retinal light sensitivity, supporting its role in the light–dark adaptation process. The study results suggest that melatonin regulates retinal light sensitivity by influencing neurotransmitter release in the retina. This study not only validates the important role of melatonin in the regulation of retinal light sensitivity but also demonstrates the application potential of computer vision technology in medical image analysis, providing a theoretical foundation for further research on the application of melatonin in retinal function.