A cost-effective computer system for identifying card counters and detecting dealer errors has been developed by a recent graduate of the University of Dundee. The Blackjack tracking system makes use of algorithms that employ methods such as contour analysis, template, and feature matching to recognize each card as it is dealt.
"Computer vision was one of the options when it came to choosing subjects for our final year, and when it came to our final project, I started to think about combining what I was learning with something I was interested in," says Dundee graduate Kris Zutis. A live feed of a game is captured by stereo cameras, which track the game as it progresses, monitor the cards along with the player, and track the betting patterns. The algorithms analyze the correlation between the player's betting patterns and the game card count to determine that a player is card counting and alert the casino staff.
Zutis is scheduled to present a research paper on the computer vision system at the International Conference on Computer Vision Systems in Liege, Belgium. "My system needs work to be commercially viable, but the potential has been demonstrated, and hopefully appearing at the event will help generate some interest in helping me to develop it further," he says.
From University of Dundee
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