"Solving Sudoku Puzzles Automatically with OpenCV & Python"

Sudoku Solver using OpenCV & Python

Sudoku is a popular and enjoyable puzzle game that requires logic and knowledge of the given numbers in order to create a solution. In this article, we will explain how you can use OpenCV and Python to develop a Sudoku solver for automatic solution.

What is OpenCV?

OpenCV (Open Source Computer Vision Library) is a library of algorithms designed for computer vision applications. It provides several hundred functions related to image processing, ranging from basic geometric operations to analytical object recognition. This library can be used to detect and match features, detect certain objects, detect motion, and much more.

How Does Sudoku Solver Work?

The goal of a Sudoku solver is to take an image of a partially filled in grid and identify all the digits within it. Once all the digits are identified, the program should be able to solve the puzzle. This process typically involves detecting the Sudoku borders, segmenting the grid into individual cells, recognizing each cell's contents, and then solve the puzzle using a traditional backtracking algorithm.

Implementation

To implement the Sudoku solver using OpenCV and Python, we need to do the following:

• Read the input image containing the grid.
• Preprocess the image to make the grid easier to detect.
• Detect the borders of the Sudoku grid.
• Segment the grid into individual cells.
• Recognize the contents of each cell.
• Input the recognized data into the backtracking algorithm.
• Output the solution.

Example code to get you started with loading an image using OpenCV:

import cv2

# Load the image of the Sudoku puzzle
sudoku = cv2.imread('sudoku.jpg')

# Display the image
cv2.imshow('Sudoku', sudoku)
cv2.waitKey(0)
cv2.destroyAllWindows()

In the above code, we first import the cv2 module from the OpenCV library. We then use the imread() function to load the image of the Sudoku puzzle from a file. The imread() function returns a numpy array that represents the image.

We then use the imshow() function to display the image in a new window. We use the waitKey() function to wait for a key press before closing the window. Finally, we use the destroyAllWindows() function to close all the open windows.

Note that you will need to install the OpenCV library using pip before running the above code. You can do so by running the following command in your terminal or command prompt:

pip install opencv-python

While this code only displays the image, you can build upon this code to implement the remaining steps involved in solving Sudoku using OpenCV & Python.

Conclusion

Using OpenCV and Python, we can develop a Sudoku solver to help solve puzzles quickly and accurately. This implementation involves recognizing individual cells’ contents, segmenting the grid, preprocessing the image and inputting the data into a backtracking algorithm. With this tool, you can save time and effectively solve puzzles automatically.