Abstract
In this paper, we introduce image-based word clouds as a novel tool for a quick and aesthetic overviews of common words in collections of digitized text manuscripts. While OCR can be used to enable summaries and search functionality to printed modern text, historical and handwritten documents remains a challenge. By segmenting and counting word images, without applying manual transcription or OCR, we have developed a method that can produce word or tag clouds from document collections. Our new tool is not limited to any specific kind of text. We make further contributions in ways of stop-word removal, class based feature weighting and visualization. An evaluation of the proposed tool includes comparisons with ground truth word clouds on handwritten marriage licenses from the 17th century and the George Washington database of handwritten letters, from the 18th century. Our experiments show that image-based word clouds capture the same information, albeit approximately, as the regular word clouds based on text data.
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Acknowledgments
This project is a part of q2b, From quill to bytes, a framework program sponsored by the Swedish Research Council (Dnr 2012-5743) and Uppsala university. The work is done in part as a collaboration with the Swedish Museum of Natural History (Naturhistoriska riksmuseet). We would also like to thank Alicia Fornés and the Document Analysis group of the Computer Vision Center at Universitat Autnoma de Barcelona for access to the BH2M dataset.
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Wilkinson, T., Brun, A. (2015). Visualizing Document Image Collections Using Image-Based Word Clouds. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9474. Springer, Cham. https://doi.org/10.1007/978-3-319-27857-5_27
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DOI: https://doi.org/10.1007/978-3-319-27857-5_27
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