Evaluating SEE: a benchmarking system for document page segmentation

Abstract

The decomposition of a document into segments such as text regions and graphics is a significant part of the document analysis process. The basic requirement for rating and improvement of page segmentation algorithms is systematic evaluation. The approaches known from the literature have the disadvantage that manually generated reference data (zoning ground truth) are needed for the evaluation task. The effort and cost of the creation of these data are very high. This paper describes the evaluation system SEE and presents an assessment of its quality. The system requires the OCR generated text and the original text of the document in correct reading order (text ground truth) as input. No manually generated zoning ground truth is needed. The implicit structure information that is contained in the text ground truth is used for the evaluation of the automatic zoning. Therefore, an assignment of the corresponding text regions in the text ground truth and those in the OCR generated text (matches) is sought. A fault tolerant string matching algorithm underlies a method, able to tolerate OCR errors in the text. The segmentation errors are determined as a result of the evaluation of the matching. Subsequently, the edit operations which are necessary for the correction of the recognized segmentation errors are computed to estimate the correction costs. Furthermore, SEE provides a version of the OCR generated text, which is corrected from the detected page segmentation errors.