Quality evaluation of document segmentation results

Summary form only given, as follows. Increasing the performance of document analysis systems requires a detailed quality evaluation of the achieved results. By focussing on segmentation algorithms, we point out that the results produced from the module under consideration should be evaluated directly; we show that the text based evaluation method which is often used in the document analysis domain is not sufficient for the purpose of a detailed quality evaluation of the segmentation module. Therefore, we propose a general evaluation approach for comparing segmentation results which is based on the segments directly. This approach is able to handle both algorithms which produce complete segmentations (partition) and algorithms which only extract objects of interest (extraction). Classes of errors are defined in a systematic way and frequencies for each class can be computed. The evaluation approach is applicable to segmentation or extraction algorithms in a wide range. We have chosen the character segmentation task as an example to demonstrate the applicability of our evaluation approach and we suggest applying our approach to other segmentation tasks.