About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
Pattern Recognition
Paper
Pink panther: A complete environment for ground-truthing and benchmarking document page segmentation
Abstract
We describe a new approach for the automatic evaluation of document page segmentation algorithms. Unlike techniques that rely on OCR output, our method is region-based: segmentation quality is assessed by comparing the segmentation output, described as a set of regions, to the corresponding ground-truth. Error maps are used to keep track of all the errors associated with each pixel, regardless of the document complexity. Misclassifications, splitting, and merging of regions are among the errors detected by the system. Each error can be weighted individually and the system can be customized to benchmark virtually any type of segmentation task. © 1998 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.