Features for Neural Net Based Region Identification of Newspaper Documents
Several features for neural network based document region identification are tested. Specifically, this paper examines features for non-text region identification. The neural network based region identification algorithm is a key component of a document recognition system that segments a document into regions, classifies them into text, graphic, photo, and other region types, and then uses this classification to guide the processing and analysis of the image. The input data are unusually challenging: low quality images of newspaper documents obtained from microfilmed archives. The results compare favorably with other results reported in the literature.
Andersen, Tim and Zhang, Wei. (2003). "Features for Neural Net Based Region Identification of Newspaper Documents". Proceedings on the Seventh International Conference on Document Analysis and Recognition, 1403-407. http://dx.doi.org/10.1109/ICDAR.2003.1227698