  Automated text detection is a difficult computer vision task. In order to
accurately detect and identity text in an image or video, two major problems
must be addressed. The primary problem is implementing a robust and reliable
method for distinguishing text vs non-text regions in images and videos. Part
of the difficulty stems from the almost unlimited combinations of fonts,
lighting conditions, distortions, and other variations that can be found in
images and videos. This paper explores key properties of two popular and proven
methods for implementing text detection; maximum stable external regions (MSER)
and stroke width variation.
