  Text line detection and localization is a crucial step for full page document
analysis, but still suffers from heterogeneity of real life documents. In this
paper, we present a new approach for full page text recognition. Localization
of the text lines is based on regressions with Fully Convolutional Neural
Networks and Multidimensional Long Short-Term Memory as contextual layers. In
order to increase the efficiency of this localization method, only the position
of the left side of the text lines are predicted. The text recognizer is then
in charge of predicting the end of the text to recognize. This method has shown
good results for full page text recognition on the highly heterogeneous Maurdor
dataset.
