This week, I had been testing some code with OpenCV on a random Sudoku board image I pulled from the internet. I made the image grayscale and applied adaptive thresholding to make the text black and background white. I was struggling with isolating the Sudoku board and detecting each cell before our team dropped the image processing idea.
After discussion with our advisors, our team decided that the camera idea did not make sense for our use case. Rather, we would implement a capacitive touch sensor grid that would make the Sudoku board more interactive and intuitive. This would give our project more hardware complexity and on the software side, allow us to focus more on the unique part of our project: the hint algorithm and projection.
My focus shifted towards the projection implementation after dropping the CV aspect. I am now looking into using Pygame, which is a Python library that already has tools for handling graphics, animations, and user inputs. It works with Raspberry Pi and GPIO inputs such as our numpad and buttons and updates the projection in real-time when the user makes an input.
The social factor that our project meets is for physical and cognitive accessibility. Individuals who may have difficulty with fine motor skills such as handwriting will have an easier time interacting with our board, and those with visual impairments can see easier on our large board display. Our Sudoku algorithm is aimed to help people of all skill levels and teach users how to work through a Sudoku puzzle and improve their problem solving skills.