Uses OpenCV to play SET, a card game where the goal is to find three cards where each "feature" - number, color, shape, shading - are all the same, or all different.
The first step is to segment the cards. We do this by thresholding the image, then running a contour detection algorithm which gives the outline of each "region". Then we find the largest twelve rectangular contours, which finds the cards relatively reliably. Finally, we run a perspective transformation to unwarp the cards.
To find how many shapes there are on one card, we run the contour detection again on that single card. After filtering out contours that are too small (noise), we simply count the number of contours.
We find the average color of a segmented contour, and compare it to prerecorded values for red, green and purple. Color detection sometimes errors, because red and purple can be mistaken for one another under different lighting conditions.
We run OpenCV's moments function on one of the segmented contours, which gives various
characteristics of the shape. We then compare the result to prerecorded values to determine
whether the card is a squiggle, diamond or ellipse.
This is done by finding how much of the card is colored. A solid-shaded card will have more colored pixels than a striped or empty-shaded card. We also run a Sobel edge-detection algorithm; a large number of edge pixels indicates that the card is striped.
This is the easiest part - just a complete search on all possible SETs.