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Proceedings Paper

A robust stamp detection framework on degraded documents
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Paper Abstract

Detecting documents with a certain stamp instance is an effective and reliable way to retrieve documents associated with a specific source. However, this unique problem has essentially remained unaddressed. In this paper, we present a novel stamp detection framework based on parameter estimation of connected edge features. Using robust basic-shape detectors, the approach is effective for stamps with analytically shaped contours, when only limited samples are available. For elliptic/circular stamps, it efficiently exploits the orientation information from pairs of edge points to determine its center position and area, without computing all the five parameters of an ellipse. In our approach, we considered the set of unique characteristics of stamp patterns. Specifically, we introduced effective algorithms to address the problem that stamps often spatially overlay their background contents. These give our approach significant advantages in detection accuracy and computation complexity over traditional Hough transform method in locating candidate ellipse regions. Experimental results on real degraded documents demonstrated the robustness of this retrieval approach on large document database, which consists of both printed text and handwritten notes.

Paper Details

Date Published: 16 January 2006
PDF: 9 pages
Proc. SPIE 6067, Document Recognition and Retrieval XIII, 60670B (16 January 2006); doi: 10.1117/12.643537
Show Author Affiliations
Guangyu Zhu, Univ. of Maryland, College Park (United States)
Stefan Jaeger, Univ. of Maryland, College Park (United States)
David Doermann, Univ. of Maryland, College Park (United States)

Published in SPIE Proceedings Vol. 6067:
Document Recognition and Retrieval XIII
Kazem Taghva; Xiaofan Lin, Editor(s)

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