On defining signatures for the retrieval and the classification of graphical drop caps

Pareti, Rudolf; Uttama, Surapong; Salmon, Jean-Pierre; Ogier, Jean-Marc; Tabbone, Salvatore; Wendling, Laurent; Adam, Sébastien; Vincent, Nicole

doi:10.1109/dial.2006.29

Cited by 7 publications

(3 citation statements)

References 8 publications

(5 reference statements)

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“…2) and can be viewed as a binary image composed of strokes. Some studies ( [14,20,25,6]) have attempted to characterize this kind of graphic image. Discussions with our historian partners in the NaviDoMass project enable us to understand how historians decompose lettrines.…”

Section: Description Of the Lettrinesmentioning

confidence: 99%

“…Selection of the shape that corresponds to the character. This work is inspired by [20,21,10] who used a Wold decomposition on the one hand, and a Zipf law on the other hand, to extract the elements of drop caps. Our paper is organized as follows: first of all, we illustrate features of lettrines, in order to highlight the difficulty of extracting a letter.…”

Section: Introductionmentioning

confidence: 99%

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Towards historical document indexing: extraction of drop cap letters

Coustaty

Pareti

Vincent

et al. 2011

IJDAR

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This paper deals with the difficult problem of indexing ancient graphic images. It tackles the particular case of indexing dropcaps (also called Lettrines), and specifically considers the problem of letter extraction from this complex graphic images. Based on an analysis of the features of the images to be indexed, an original strategy is proposed. This approach relies on filtering the relevant information, on the basis of Meyer decomposition. Then, in order to accommodate the variability of representation of the information, a Zipf law modeling enables detection of the regions belonging to the letter, what allows it to be segmented. The overall process is evaluated using a relevant set of images, which shows the relevance of the approach.

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Section: Description Of the Lettrinesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Towards historical document indexing: extraction of drop cap letters

Coustaty

Pareti

Vincent

et al. 2011

IJDAR

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“…impressions, ornamental cap...) [1]. Some systems propose to index these databases [6,2,11]. Once similar images have been retrieved either automatically or manually, it can be difficult to notice visually the relevant differences.…”

Section: Introductionmentioning

confidence: 99%

A Method for Image Local-Difference Visualization

Baudrier

Riffaud

2007

Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 2

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As ancient documents are being digitized, systems for retrieving documents or images can now be found in Digital Libraries. With regard to illustrations, the content-based image retrieval is difficult and the user often needs to check visually the similarity of the retrieved images. This process is not entirely reliable since very similar images (impressions, ornamental letters) can actually be printed from distinct stamps. No other visualization method exists than the map of pixelto-pixel gray level difference (PPDMap). We propose here a method that evaluates locally the differences and allows the user to visualize them. It is based on a local adaptation of the Hausdorff distance. Our method performance is successfully compared to the PPDMap and an expert difference evaluation assesses our method reliability.

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