PSET: A Page Segmentation Evaluation Toolkit

Empirical performance evaluation of page segmentation algorithms has become increasingly important due to the numerous algorithms that are being proposed each year. In order to choose between these algorithms for a specific domain it is important to empirically evaluate their performance. To accomplish this task the document image analysis community needs i) standardized document image datasets with groundtruth, ii) evaluation metrics that are agreed upon by researchers, and iii) freely available software for evaluating new algorithms and replicating other researchers’ results. In an earlier paper (SPIE Document Recognition and Retrieval 2000) we published evaluation results for various popular page segmentation algorithms using the University of Washington dataset. In this paper we describe the PSET evaluation package, which was used to evaluate the segmentation algorithms. The description of the package will allow researchers to understand the software better, replicate our results, evaluate new algorithms, experiment with new metrics and datasets, etc. The software is written using the C language on the SUN/UNIX platform and is being made available to researchers at no cost.