The bag-of-words (BOW) model is the common approach for classifying documents, where words are used as feature for training a classifier. This generally involves a huge number of features. Some techniques, such as Latent Semantic Analysis (LSA) or Latent Dirichlet Allocation (LDA), have been designed to summarize documents in a lower dimension with the least semantic information loss. Some sema...

In this work we investigate some technical questions related to the application of neural networks in document classification. First, we discuss the effects of different averaging protocols for the 2 statistic used to remove non-informative terms. This is an especially relevant issue for the neural network technique, which requires an aggressive dimensionality reduction to be feasible. Second, ...

ÐTo maintain OCR accuracy with decreasing quality of page image composition, production, and digitization, it is essential to tune the system to each document. We propose a prototype extraction method for document-specific OCR systems. The method automatically generates training samples from unsegmented text images and the corresponding transcripts. It is tolerant of transcription errors, so a ...

Automatic handwritten script identification from document images facilitates many important applications such as sorting, transcription of multilingual documents and indexing of large collection of such images, or as a precursor to optical character recognition (OCR). In this paper, we investigate a texture as a tool for determining the script of handwritten document image, based on the observa...