Title :
A Generic Method for Stamp Segmentation Using Part-Based Features
Author :
Ahmed, Shehab ; Shafait, Faisal ; Liwicki, Marcus ; Dengel, Andreas
Author_Institution :
German Res. Center for Artificial Intell. (DFKI), Kaiserslautern, Germany
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.
Keywords :
document image processing; image segmentation; shape recognition; document images; generic method; part-based features; shape based techniques; stamp detection; stamp extraction; stamp segmentation; stamp verification; Detectors; Feature extraction; Image color analysis; Image segmentation; Seals; Shape; Training;
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2013 12th International Conference on
Conference_Location :
Washington, DC
DOI :
10.1109/ICDAR.2013.145