Document seal detection using GHT and character proximity graphs

Partha Pratim Roy, Umapada Pal, Josep Lladós

Research output: Contribution to journalArticleResearchpeer-review

28 Citations (Scopus)


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 Experiment is performed in an archive of historical documents of handwritten/printed English text.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. © 2010 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)1282-1295
JournalPattern Recognition
Issue number6
Publication statusPublished - 1 Jun 2011


  • Generalized Hough transform
  • Graphical symbol spotting
  • Multi-oriented character recognition
  • Seal recognition


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