Interpreting information contained in images has long been a difficult problem in data mining, but it is one that is really starting to be addressed. The latest research is providing algorithms to detect and understand images to the point where automated commercial surveillance systems are now being used—in real-world scenarios—by major vendors. These systems are capable of understanding and recognizing objects and people in video footage.

It is difficult to extract information from images. There is lots of raw data in an image, and the standard method for encoding images—pixels—isn't that informative by itself. Images—particularly photos—can be blurry, too close to the targets, too dark, too light, scaled, cropped, skewed, or any other of a variety of problems that cause havoc for a computer system trying to extract useful information.

In this chapter, we look at extracting text from images by using neural networks for predicting each letter...