Empirical performance evaluation of page segmentation algorithms

Song Mao; Tapas Kanungo

doi:10.1117/12.373507

22 December 1999 Empirical performance evaluation of page segmentation algorithms

Song Mao, Tapas Kanungo

Proceedings Volume 3967, Document Recognition and Retrieval VII; (1999) https://doi.org/10.1117/12.373507
Event: Electronic Imaging, 2000, San Jose, CA, United States

Abstract

Document page segmentation is a crucial preprocessing step in Optical Character Recognition (OCR) system. While numerous segmentation algorithms have been proposed, there is relatively less literature on comparative evaluation -- empirical or theoretical -- of these algorithms. We use the following five step methodology to quantitatively compare the performance of page segmentation algorithms: (1) First we create mutually exclusive training and test dataset with groundtruth, (2) we then select a meaningful and computable performance metric, (3) an optimization procedure is then used to automatically search for the optimal parameter values of the segmentation algorithms, (4) the segmentation algorithms are then evaluated on the test dataset, and finally (5) a statistical error analysis is performed to give the statistical significance of the experimental results. We apply this methodology to five segmentation algorithms, three of which are representative research algorithms and the rest two are well-known commercial products. The three research algorithms evaluated are: Nagy's X-Y cut, O'Gorman's Docstrum and Kise's Voronoi-diagram-based algorithm. The two commercial products evaluated are: Caere Corporation's segmentation algorithm and ScanSoft Corporation's segmentation algorithm. The evaluations are conducted on 978 images from the University of Washington III dataset. It is found that the performance of the Voronoi-based, Docstrum and Caere's segmentation algorithms are not significantly different from each other, but they are significantly better than ScanSoft's segmentation algorithm, which in turn is significantly better than the performance of the X-Y cut algorithm. Furthermore, we see that the commercial segmentation algorithms and research segmentation algorithms have comparable performances.

Citation Download Citation

Song Mao and Tapas Kanungo "Empirical performance evaluation of page segmentation algorithms", Proc. SPIE 3967, Document Recognition and Retrieval VII, (22 December 1999); https://doi.org/10.1117/12.373507

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