4 February 2013 Semi-structured document image matching and recognition
Author Affiliations +
This article presents a method to recognize and to localize semi-structured documents such as ID cards, tickets, invoices, etc. Standard object recognition methods based on interest points work well on natural images but fail on document images because of repetitive patterns like text. In this article, we propose an adaptation of object recognition for image documents. The advantages of our method is that it does not use character recognition or segmentation and it is robust to rotation, scale, illumination, blur, noise and local distortions. Furthermore, tests show that an average precision of 97.2% and recall of 94.6% is obtained for matching 7 different kinds of documents in a database of 2155 documents.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Olivier Augereau, Nicholas Journet, Jean-Philippe Domenger, "Semi-structured document image matching and recognition", Proc. SPIE 8658, Document Recognition and Retrieval XX, 865804 (4 February 2013); doi: 10.1117/12.2003911; https://doi.org/10.1117/12.2003911


Object recognition and matching for image retrieval
Proceedings of SPIE (July 31 2002)
Shape representation for content-based image retrieval
Proceedings of SPIE (May 30 2000)
Detecting multicolored object in image by content
Proceedings of SPIE (September 25 1998)
Error measures for object-based image compression
Proceedings of SPIE (September 16 2005)

Back to Top