The zonemap metric for page segmentation and area classification in scanned documents

Abstract

A novel metric for the detection and classification of different areas in scanned documents is presented in this paper. This metric, ZoneMap, aims at evaluating both page segmentation and zone classification. Moreover, for the segmentation sub-task, it handles the superposition of overlapping zones. These characteristics allow to evaluate systems in a coherent way using a single ZoneMap metric. Weights assigned to different parameters add flexibility and allow for fine-tuning of the metric in order to reflect the specificity of a particular applicative context. ZoneMap was experimented in the Maurdor evaluation campaigns where it is used as a primary metric for page segmentation and area classification. Evaluation results show that ZoneMap provides additional ways to assess system performance and analyze the results. ZoneMap is implemented in a publicly available LNE maurdor-eval evaluation toolkit that is distributed under the GPL license.