@InProceedings{ParthaPratimRoy2010,
author="Partha Pratim Roy
and Umapada Pal
and Josep Llados",
title="Seal Object Detection in Document Images using GHT of Local Component Shapes",
booktitle="10th ACM Symposium On Applied Computing",
year="2010",
pages="23--27",
abstract="Due to noise, overlapped text/signature and multi-oriented nature, seal (stamp) object detection involves a difficult challenge. This paper deals with automatic detection of seal from documents with cluttered background. Here, a seal object is characterized by scale and rotation invariant spatial feature descriptors (distance and angular position) computed from recognition result of individual connected components (characters). Recognition of multi-scale and multi-oriented component is done using Support Vector Machine classifier. Generalized Hough Transform (GHT) is used to detect the seal and a voting is casted for finding possible location of the seal object in a document based on these spatial feature descriptor of components pairs. The peak of votes in GHT accumulator validates the hypothesis to locate the seal object in a document. Experimental results show that, the method is efficient to locate seal instance of arbitrary shape and orientation in documents.",
optnote="DAG",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=1291), last updated on Fri, 28 Feb 2014 09:54:51 +0100",
doi="10.1145/1774088.1774094",
opturl="http://dl.acm.org/citation.cfm?doid=1774088.1774094"
}