Discrimination Between Digits and Outliers in Handwritten Documents Applied to the Extraction of Numerical Fields
Abstract
In this article, we propose a numerical field extraction system from unconstrained handwritten documents. The system is based on a segmentation driven by recognition stage followed by a syntactical analysis which detects the sequences that may compose a numerical field. We focus here on the design of a digit classifier embedded in the segmentation/ recognition process able to discriminate digits from outliers such as words, fragment of words, noise, etc. For that, we have developed a light classifier used as prior to a standard digit classifier in order to reject “obvious outliers”. Several classifiers have been compared in terms of ROC curve and processing time.
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