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2010
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Font retrieval on a large scale: An experimental study

9 years 11 months ago
Font retrieval on a large scale: An experimental study
This paper addresses the problem of font retrieval using a query-by-example paradigm: given a font, retrieve the the most visually similar fonts. We describe a font by (a) rendering a set of reference characters, (b) extracting a feature vector for each reference character and (c) concatenating thelevel character descriptors. The similarity between two fonts is simply the similarity between the vectorial representations. Our contribution is an experimental comparison of characterlevel descriptors of step (b) on a large dataset of 9,000 fonts. The descriptors we chose to evaluate were drawn from the literature on typed and handwritten text analysis. An important conclusion is that the SIFT descriptor, which was shown to be state-of-the-art for object recognition in photographs and for handwriting recognition, yields the best results for font retrieval.
Saurabh Kataria, Luca Marchesotti, Florent Perronn
Added 12 Feb 2011
Updated 12 Feb 2011
Type Journal
Year 2010
Where ICIP
Authors Saurabh Kataria, Luca Marchesotti, Florent Perronnin
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