How to Remove Convexity Defects from a Sudoku Grid for Accurate Image Processing?

Resolving Convexity Defects in a Sudoku Grid

When capturing Sudoku images, occasional defects can arise, manifesting as convexities in the grid boundary. This article addresses this issue, discussing methods to remove these defects before performing further processing on the image.

Convexity Defects in Sudoku Images

The presence of convexities in the Sudoku grid boundary can prevent accurate warping, leading to distortions in the resulting image. This can hinder subsequent operations such as OCR and digit recognition.

Proposed Solution: Image Normalization

To remove convexities, the following steps are recommended:

1. Brightness Adjustment: Adjust the image's brightness by dividing each pixel by the result of a morphological closing operation. This enhances contrast and suppresses background noise.
2. Component Analysis: Perform connected component analysis to identify the Sudoku grid region and discard the background. Choose the component with the largest convex area.
3. Masking: Create a mask representing the Sudoku grid by filling the identified component.
4. Vertical and Horizontal Line Detection: Use second-order derivative filters to detect vertical and horizontal lines within the masked image.
5. Component Selection: Apply connected component analysis to extract the grid lines from the filtered images, selecting only components with sufficient length.
6. Intersection Calculation: Intersect the vertical and horizontal grid line masks to obtain the intersection points. These points represent the grid line intersections.
7. Interpolation Functions: Create interpolation functions for X/Y mapping based on the grid line intersections.
8. Image Transformation: Use these interpolation functions to transform the original image, yielding a corrected grid boundary.

By following these steps, the convexity defects in the Sudoku image can be removed, enabling subsequent processing to proceed accurately.

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