GREC 2007 Arc Segmentation Contest: Evaluation of Four Participating Algorithms
Graphics Recognition. Recent Advances and New Opportunities
Page frame detection for marginal noise removal from scanned documents
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
IAMonDo-database: an online handwritten document database with non-uniform contents
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Textline information extraction from grayscale camera-captured document images
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Image segmentation algorithms based on the machine learning of features
Pattern Recognition Letters
GREC'09 arc segmentation contest: performance evaluation on old documents
GREC'09 Proceedings of the 8th international conference on Graphics recognition: achievements, challenges, and evolution
MAST: multi-script annotation toolkit for scenic text
Proceedings of the 2011 Joint Workshop on Multilingual OCR and Analytics for Noisy Unstructured Text Data
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This paper presents a new representation and evaluation procedure of page segmentation algorithms and analyzes six widely-used layout analysis algorithms using the procedure. The method permits a detailed analysis of the behavior of page segmentation algorithms in terms of over- and undersegmentation at different layout levels, as well as determination of the geometric accuracy of the segmentation. The representation of document layouts relies on labeling each pixel according to its function in the overall segmentation, permitting pixel-accurate representation of layout information of arbitrary layouts and allowing background pixels to be classified as "don't care". Our representations can be encoded easily in standard color image formats like PNG, permitting easy interchange of segmentation results and ground truth.