(untitled) (Eureka Journal of Artificial Intelligence and Data Innovation, 2026)
In this paper, an automated system based on C, RQ, and DoG (Difference of Gaussian) metrics is developed to assess the quality of digital images. Using the Python programming language and the OpenCV library, all image files in the image folder are analyzed, and C, RQ, and DoG values are calculated for each image. The results allow us to evaluate the sharpness, edge level, and clarity of images using objective numerical indicators. The DoG metric is used to visually display an additional clarity map and its value distribution. This approach is of practical importance in computer vision, image processing, and scientific research.