An Introduction to Pattern Recognition (Repost)

Pattern Classification, more often called Pattern Recognition, is the primary bottleneck in the task of automation. Robots without sensors have their uses, but they are limited and dangerous. In fact one might plausibly argue that a robot without sensors isn't a realrobot at all, whatever the hardware manufacturers may say. But equipping a robot with vision is easy only at the hardware level. It is neither expensive nor technically difficult to connect a camera and frame grabber board to a computer, the robot's `brain'. The problem is with the software, or more exactly with the algorithms which have to decide what the robot is looking at; the input is an array of pixels, coloured dots, the software has to decide whether this is an image of an eggshell or a teacup. A task which human beings can master by age eight, when they decode the firing of the different light receptors in the retina of the eye, this is computationally very difficult, and we have only the crudest ideas of how it is done. At the hardware level there are marked similarities between the eye and a camera (although there are differences too). At the algorithmic level, we have only a shallow understanding of the issues.