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Semi-structured document image matching and recognition

Abstract : This article presents a method to recognize and to localize semi-structured documents such as ID cards, tickets, invoices, etc. 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 di erent kinds of documents in a database of 2155 documents.
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Contributor : Olivier Augereau Connect in order to contact the contributor
Submitted on : Wednesday, November 21, 2012 - 6:26:15 PM
Last modification on : Monday, December 20, 2021 - 4:50:11 PM
Long-term archiving on: : Friday, February 22, 2013 - 3:50:40 AM


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  • HAL Id : hal-00755748, version 1



Olivier Augereau, Nicholas Journet, Jean-Philippe Domenger. Semi-structured document image matching and recognition. Document Recognition and Retrieval, Feb 2013, San Fransisco, United States. pp.1-12. ⟨hal-00755748⟩



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