Image Detection and Digit Recognition to solve Sudoku as a Constraint Satisfaction Problem
This work addresses Sudoku solving for puzzle enthusiasts and researchers, but it is incremental as it combines existing methods with new feature extraction.
The paper tackled the problem of solving Sudoku puzzles by converting images into digit arrays and applying constraint satisfaction techniques, resulting in decreased search time by eliminating inconsistent values.
Sudoku is a puzzle well-known to the scientific community with simple rules of completion, which may require a com-plex line of reasoning. This paper addresses the problem of partitioning the Sudoku image into a 1-D array, recognizing digits from the array and representing it as a Constraint Sat-isfaction Problem (CSP). In this paper, we introduce new fea-ture extraction techniques for recognizing digits, which are used with our benchmark classifiers in conjunction with the CSP algorithms to provide performance assessment. Experi-mental results show that application of CSP techniques can decrease the solution's search time by eliminating incon-sistent values from the search space.