A robust stamp detection framework on degraded documents

Guangyu Zhu; Stefan Jaeger; David Doermann

doi:10.1117/12.643537

16 January 2006 A robust stamp detection framework on degraded documents

Guangyu Zhu, Stefan Jaeger, David Doermann

Proceedings Volume 6067, Document Recognition and Retrieval XIII; 60670B (2006) https://doi.org/10.1117/12.643537
Event: Electronic Imaging 2006, 2006, San Jose, California, United States

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.

Citation Download Citation

Guangyu Zhu, Stefan Jaeger, and David Doermann "A robust stamp detection framework on degraded documents", Proc. SPIE 6067, Document Recognition and Retrieval XIII, 60670B (16 January 2006); https://doi.org/10.1117/12.643537

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available