Camera-based document image matching using multi-feature probabilistic information fusion

A common requirement in camera-based document matching and retrieval systems, is to retrieve a document whose image has been taken under difficult imaging conditions (insufficient and non-uniform illumination, skew, occlusions, all of these possibly coming in together in the same image). We present a system for robust matching and retrieval which works well for such difficult query images, using probabilistic information fusion from multiple independent sources of measurement. Our experiments with two robust and computationally inexpensive features show promising results on a representative database, compared with the state-of-the-art in the area.