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Segmentation and Redundancy Analysis in Text Layout and Clustering Techniques

This project focuses on the segmentation and redundancy analysis of text, graphics, and layout using various clustering techniques. We explore methods for breaking down text into chars, words, lines, and punctuation, leveraging physical layouts like ALTO. Key tasks include clustering data into XML files, conducting redundancy analysis, and revising clusters derived from visual content. Additionally, we address exploitation aspects, including typo analysis, visualization, and the integration of metadata standards such as TEI and ALTO within transcription and indexing processes.

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Segmentation and Redundancy Analysis in Text Layout and Clustering Techniques

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  1. WP1 : Segmentation and Redundancy analysis WP1.1 WP1.2 WP1.3 Layout AGORA Segmentation of char, words, lines, punctuation, accents, … Clustering techniques Images Users WP1.1.1 WP1.3.1 Physical Layout (Alto) Text, graphics, lines, words, chars Redundancy (XML) Clusters (1 fichier XML/cluster,Bbox) + Page statistics WP2 : Segmentation and Redundancy Exploitation WP2.1 WP2.4 WP2.2 WP2.3 Cluster revision & Typo analysis Visualization, interaction RETRO Cluster recognition (OCROpus, …) Spotting Knowledge (Dictionary, Lexicon, …) WP2.5 WP2.5 Transcription, indexation, meta-data (TEI, ALTO, …) Learning dataset & Fonts (XML, Images, …)

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