Text segmentation using Gabor filters for automatic document processing
Machine Vision and Applications - Special issue: document image analysis techniques
Segmentation of page images using the area Voronoi diagram
Computer Vision and Image Understanding - Special issue on document image understanding and retrieval
The Document Spectrum for Page Layout Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Encoding of Modified X-Y Trees for Document Classification
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Page Segmentation for Manhattan and Non-Manhattan Layout Documents via Selective CRLA
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Distance Measures for Layout-Based Document Image Retrieval
DIAL '06 Proceedings of the Second International Conference on Document Image Analysis for Libraries
International Journal on Document Analysis and Recognition
Performance comparison of six algorithms for page segmentation
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
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Document classification is an important task in all the processes related to document storage and retrieval. In the case of complex documents, structural features are needed to achieve a correct classification. Unfortunately, physical layout analysis is error prone. In this paper we present a pre-segmentation step based on a divide & conquer strategy that can be used to improve the page segmentation results, independently of the segmentation algorithm used. This pre-segmentation step is evaluated in classification and retrieval using the selective CRLA algorithm for layout segmentation together with a clustering based on the voronoi area diagram, and tested on two different databases, MARG and Girona Archives.