Detection of Sudoku puzzle using image processing and solving by Backtracking, Simulated Annealing and Genetic Algorithms: A comparative analysis

Abstract

In this paper, we propose the digital detection and decryption of a sudoku puzzle using vision based techniques and subsequent solving of the puzzle using three algorithms-Backtracking, Simulated Annealing and Genetic Algorithm. The proposed method can recognize any sudoku puzzle captured from a digital camera and after employing appropriate pre-processing algorithms which include adaptive thresholding, Hough Transform and geometric transformation, the digits are recognized using Optical Character Recognition (OCR), and based on their pixel locations in the image, they are stored in corresponding locations in the 9×9 matrix. The detected puzzles of varying complexity levels are then solved using the three algorithms and the results are compared and contrasted, indicating the relative efficiencies of the three techniques in accurately solving Sudoku puzzles. Simulated Annealing performed the best amongst the three algorithms, whereas, genetic algorithm performed the worst in the comparison.

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Cite this paper

@article{Kamal2015DetectionOS, title={Detection of Sudoku puzzle using image processing and solving by Backtracking, Simulated Annealing and Genetic Algorithms: A comparative analysis}, author={Snigdha Kamal and Simarpreet Singh Chawla and Nidhi Goel}, journal={2015 Third International Conference on Image Information Processing (ICIIP)}, year={2015}, pages={179-184} }