Rotation-robust math symbol recognition and retrieval using outer contours and image subsampling

Siyu Zhu; Lei Hu; Richard Zanibbi

doi:10.1117/12.2008383

4 February 2013 Rotation-robust math symbol recognition and retrieval using outer contours and image subsampling

Siyu Zhu, Lei Hu, Richard Zanibbi

Proceedings Volume 8658, Document Recognition and Retrieval XX; 865805 (2013) https://doi.org/10.1117/12.2008383
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

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.

Citation Download Citation

Siyu Zhu, Lei Hu, and Richard Zanibbi "Rotation-robust math symbol recognition and retrieval using outer contours and image subsampling", Proc. SPIE 8658, Document Recognition and Retrieval XX, 865805 (4 February 2013); https://doi.org/10.1117/12.2008383

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