@Article{ParthaPratimRoy2011,
author="Partha Pratim Roy
and Umapada Pal
and Josep Llados",
title="Document Seal Detection Using Ght and Character Proximity Graphs",
journal="Pattern Recognition",
year="2011",
publisher="Elsevier",
volume="44",
number="6",
pages="1282--1295",
optkeywords="Seal recognition",
optkeywords="Graphical symbol spotting",
optkeywords="Generalized Hough transform",
optkeywords="Multi-oriented character recognition",
abstract="This paper deals with automatic detection of seal (stamp) from documents with cluttered background. Seal detection involves a difficult challenge due to its multi-oriented nature, arbitrary shape, overlapping of its part with signature, noise, etc. Here, a seal object is characterized by scale and rotation invariant spatial feature descriptors computed from recognition result of individual connected components (characters). Scale and rotation invariant features are used in a Support Vector Machine (SVM) classifier to recognize multi-scale and multi-oriented text characters. The concept of generalized Hough transform (GHT) is used to detect the seal and a voting scheme is designed for finding possible location of the seal in a document based on the spatial feature descriptor of neighboring component pairs. The peak of votes in GHT accumulator validates the hypothesis to locate the seal in a document. Experiment is performed in an archive of historical documents of handwritten/printed English text. Experimental results show that the method is robust in locating seal instances of arbitrary shape and orientation in documents, and also efficient in indexing a collection of documents for retrieval purposes.",
optnote="DAG",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=1820), last updated on Tue, 11 Mar 2014 15:55:36 +0100",
doi="http://dx.doi.org/10.1016/j.patcog.2010.12.004"
}