A Generic Method for Stamp Segmentation Using Part-Based Features

Sheraz Ahmed, Faisal Shafait, Marcus Eichenberger-Liwicki, Andreas Dengel
ICDAR, Washington, DC, USA, IEEE, 2013

Abstract:

Traditionally, stamps are considered as a seal of authenticity for documents. For automatic processing and verification, segmentation of stamps from documents is pivotal. Existing methods for stamp extraction mostly employ color and/or shape based techniques, thereby limiting their applicability to only colored and specific shape stamps. In this paper, a novel, generic method based on part-based features is presented for segmentation of stamps from document images. The proposed method can segment black, colored, unseen, arbitrary shaped, textual, as well as graphical stamps. The proposed method is evaluated on a publicly available dataset for stamp detection and verification and achieved recall and precision of 73% and 83% respectively, for black stamps which were not addressed in the past.

Files:

  StampDetectionUsingLocalFeatures-icad2013.pdf

BibTex:

@inproceedings{ AHME2013,
	Title = {A Generic Method for Stamp Segmentation Using Part-Based Features},
	Author = {Sheraz Ahmed and Faisal Shafait and Marcus Eichenberger-Liwicki and Andreas Dengel},
	BookTitle = {ICDAR},
	Year = {2013},
	Publisher = {IEEE}
}

     
Last modified:: 30.08.2016