Learn to Solve Sudoku Using OpenCV

Table of Contents

1. Introduction
2. Preprocessing the Image
3. Finding Contours
4. Finding the Sudoku
5. Applying WORD Perspective
6. Classifying Each Digit
7. Finding the Solution
8. Overlaying the Solution
9. Adding GRID Lines
10. Summary and Conclusion

Introduction

In this video Tutorial, we will learn how to solve Sudoku problems using OpenCV. We will go step by step, covering the pre-processing of the image, finding contours, classifying each digit, finding the solution, and overlaying it back to the original image. If you are interested in learning web development and how to create different projects using the web, make sure to check out my new Channel. Now, let's get started with Sudoku!

Preprocessing the Image

The first step in solving Sudoku puzzles is to preprocess the image. This involves converting the image to grayscale, applying thresholding to enhance the contrast, and performing some blurring. By doing this, we can prepare the image for further processing and improve the accuracy of our digit classification.

Finding Contours

Once our image is preprocessed, we can start finding the contours. Contours are the outlines of the Sudoku grid and its digits. We use the 'external' method to extract the outer contours and the 'simple' chain approximation to simplify their shapes. By finding the contours, we can identify the Sudoku grid within the image.

Finding the Sudoku

After finding the contours, we can locate the Sudoku Puzzle within the image. We also apply word perspective to correct any perspective distortions caused by the image angle. This ensures that the Sudoku grid appears as a perfect square, making it easier for us to work with.

Classifying Each Digit

With the Sudoku grid located, we can then classify each digit within the grid. We use a pre-trained model to predict the value of each digit using image classification techniques. By classifying each digit, we can create a representation of the Sudoku puzzle on our computer, making it easier to solve.

Finding the Solution

Once we have identified the digits within the Sudoku puzzle, we can use a Sudoku solver algorithm to find the solution. The solver algorithm analyzes the board and determines the correct values for each empty space. It ensures that the solution is logically consistent with all the known values within the puzzle.

Overlaying the Solution

After finding the solution, we overlay it back onto the original image. This allows us to Visualize the solved Sudoku puzzle. By overlaying the solution, we can compare the original image with the solved puzzle and ensure that our algorithm has correctly solved the Sudoku problem.

Adding Grid Lines

To enhance the visual appeal of the solved puzzle, we can add grid lines to divide the Sudoku grid into individual cells. This adds a professional touch to the final result and makes it easier for others to read and understand the solved puzzle.

Summary and Conclusion

In this tutorial, we have learned how to solve Sudoku puzzles using OpenCV. We have covered the steps involved in preprocessing the image, finding contours, classifying each digit, finding the solution, overlaying the solution, and adding grid lines. By following these steps, we can automatically solve Sudoku puzzles and visualize the results. Remember to check out my new channel for more web development tutorials and projects.

Highlights

• Learn how to solve Sudoku puzzles using OpenCV
• Preprocess the image to enhance the accuracy of digit classification
• Find contours to identify the Sudoku grid within the image
• Apply word perspective to correct perspective distortions
• Classify each digit using a pre-trained model
• Find the solution using a Sudoku solver algorithm
• Overlay the solution back onto the original image
• Add grid lines for a professional touch
• Summary and conclusion

FAQs

Q: What is OpenCV? A: OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning library. It provides a wide range of functions and algorithms for image and video processing, including object detection, face recognition, and image classification.

Q: Can I solve Sudoku puzzles manually without using OpenCV? A: Yes, you can solve Sudoku puzzles manually without using OpenCV. OpenCV provides a way to automate the solving process using image processing techniques, but Sudoku puzzles can also be solved manually by following logical rules and strategies.

Q: How accurate is the digit classification in Sudoku solving? A: The accuracy of digit classification depends on the quality of the pre-trained model and the training data used. With a well-trained model and sufficient training data, the classification accuracy can be high. However, it is important to note that there may still be some errors, especially in challenging cases or when the model encounters ambiguous or poorly captured digits.

Q: Is there a way to input a Sudoku puzzle directly instead of using an image? A: Yes, you can input a Sudoku puzzle directly as a matrix or an array instead of using an image. The Sudoku solver algorithm can work with a matrix representation of the puzzle and find the solution based on the input values provided.

Q: Are there any limitations to using OpenCV for Sudoku solving? A: While OpenCV provides powerful tools for image processing and analysis, it does have some limitations. For example, it may struggle with complex or distorted images, and the accuracy of the digit classification may vary depending on the quality of the input images and the training data. Additionally, OpenCV may not be the most efficient or optimal solution for all Sudoku solving scenarios, especially in cases where the puzzles have unique or unconventional designs.

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