1. A method of performing optical text recognition on an input image using a Hidden Markov Model, the method comprising: identifying a node of the Hidden Markov Model, wherein the node is a label transition node; receiving a frame, wherein the frame is a portion of the input image and wherein the frame has been determined to be a predicted character boundary in the input image; and pruning the node from a possible nodes list for the frame with label transition node pruning, wherein the possible nodes list for the frame is a list of nodes in the Hidden Markov Model that may be evaluated to determine whether they correspond to the frame, the pruning comprising: scoring the node at the frame to obtain a score, and pruning the node when the score is greater than a sum of a best score at the frame and a beam threshold minus a penalty term.