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Proceedings Paper

Rotation-robust math symbol recognition and retrieval using outer contours and image subsampling
Author(s): Siyu Zhu; Lei Hu; Richard Zanibbi
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Paper Abstract

This paper presents an unified recognition and retrieval system for isolated offline printed mathematical symbols for the first time. The system is based on nearest neighbor scheme and uses modified Turning Function and Grid Features to calculate the distance between two symbols based on Sum of Squared Difference. An unwrap process and an alignment process are applied to modify Turning Function to deal with the horizontal and vertical shift caused by the changing of staring point and rotation. This modified Turning Function make our system robust against rotation of the symbol image. The system obtains top-1 recognition rate of 96.90% and 47.27% Area Under Curve (AUC) of precision/recall plot on the InftyCDB-3 dataset. Experiment result shows that the system with modified Turning Function performs significantly better than the system with original Turning Function on the rotated InftyCDB-3 dataset.

Paper Details

Date Published: 4 February 2013
PDF: 12 pages
Proc. SPIE 8658, Document Recognition and Retrieval XX, 865805 (4 February 2013); doi: 10.1117/12.2008383
Show Author Affiliations
Siyu Zhu, Rochester Institute of Technology (United States)
Lei Hu, Rochester Institute of Technology (United States)
Richard Zanibbi, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 8658:
Document Recognition and Retrieval XX
Richard Zanibbi; Bertrand Coüasnon, Editor(s)

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