Image objects and multi-scale features for annotation detection

Details

Event ICPR 2008

Authors

Chen, Jindong D.
Eric Saund
Technical Publications
December 8th 2008
This paper investigates several issues in the problem of detecting handwritten markings, or annotations, on printed documents. One issue is to define the appropriate units over which to perform feature measurements and assign type labels. We propose an alpha-shape tree that operates across multiple scales. A second issue is to devise image features that offer inferential power for machine learning algorithms. We report on a feature that measures edge turn statistics. A third issue is how to combine local and neighborhood evidence. We exploit the alpha shape tree in a direct inference architecture. Information propagation schemes such as Markov random fields may be readily layered on top of our output.

Citation

Chen, J. D.; Saund, E.; Wang, Y. Image objects and multi-scale features for annotation detection. 19th International Conference on Pattern Recognition (ICPR 2008); 2008 December 8-11; Tampa, FL. Piscataway, NJ: IEEE; 2008.

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