Sudoku, a popular puzzle game requiring pattern recognition rather than mathematical skills, has inspired a technological approach to automate its solution using OpenCV and Python. The Sudoku Solver Project leverages computer vision, particularly through OpenCV, to enable machines to recognize and solve the puzzle autonomously. This involves a series of image processing tasks such as loading, resizing, and enhancing the puzzle image, followed by digit recognition using a Convolutional Neural Network (CNN) model. Grid extraction and contour detection are also employed to understand the puzzle structure, with the backtracking algorithm used to systematically solve the Sudoku by exploring potential solutions. This project highlights the fusion of artificial intelligence and computer vision, demonstrating the capability of computers to emulate human problem-solving techniques by efficiently solving complex puzzles.