Abstract
The area of offline handwritten text recognition(OHTR) has been widely researched in the last decades, but it stills an important research problem. The OHTR system has an objective to transform a document image into text data. Compared with online handwriting recognition, the dynamic information about the writing trajectories in OHTR is not available. Many advancements have been proposed in the literature, most notably the application of deep learning methods to OHTR. In this paper, we introduced how this problem has been handled in the past few decades, analyze the latest advancements and the potential directions for future research in this field.
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