Chocolate Tech

Elli Angelopoulou is an admitted chocoholic. She is also a doctoral student in computer science at Johns Hopkins. So it was natural that her interest in computer vision led to the development of a system that can, among other things, tell the difference between two homemade chocolates (upper left and right). Her hardware is strictly off the shelf: a desktop computer, three lightbulbs, and a black-and-white video camera. But thanks to a program she’s written, it can do what other computer recognition systems can’t: discriminate among subtly different rounded objects. Most computer vision methods depend on the detecting of edges, lines, and corners. None of these systems are applicable when we have a smooth and free-form object like a teapot, a cup, or a mug, says Angelopoulou. Her program tracks the intensity of light reflected off an object illuminated from three different directions and uses this information to measure curved ...