Bull's Head and Mermaid - The Bernstein Project - Österreichische ...

Component model Thesaurus
elongated to the jaw elongated to the muzzle / mouth
stem rod
bevel oblique
2-lobed flower or leaf two-petalled
4-lobed flower or leaf quatrefoil
templar’s cross maltese cross
threefoil trefoil
brokeness brokenness / angularity
curl noch nicht im Thesaurus
alignment noch nicht im Thesaurus
lateral noch nicht im Thesaurus
The final revision of the trilingual Thesaurus was undertaken
by comparing it with the main motif groups of Briquet.
More than thirty terms that had not yet been recorded
were added to the Thesaurus: amphora (amphore; Amphore),
board game (damier; Brettspiel), dolphin (dauphin;
Delphin), bagpipe (cornemuse; Dudelsack), lizard (lézard; Eidechse),
sickle (faucille; Sichel), candlestick (chandelier;
Kerzenleuchter), currycomb (étrille; Striegel), to name just a
few. In addition, terms that were already included had to be
adapted, as for example “escargot” (snail), which the Thesaurus
had already listed as “limarçon”. The importance of
editorial supervision can also be seen here, as the later
change also had to be taken into account in Piccard-Online.
Through the editorial work sketched above, the Thesaurus
now includes 725 terms, in German, English, and
French, that represent the key vocabulary needed to describe
watermarks. The advantage of the Thesaurus is clear:
watermarks with the same motif can now be described
with equivalent terms in English, German, and French,
which fulfils the conditions needed for comprehensive
searches in the various databases. In the framework of the
project, a PDF-file of the trilingual Thesaurus has been
made available on the Bernstein homepage so that research
in all three languages is now possible.
Literature: Palmer, Verbalizing Watermarks; Kämmerer,
Städtewappen.
E.F. (C.P.-K.)
Digital Watermark Detection and Retrieval
Introduction
Watermarks and paper features are important sources of information
to determine the dating and authenticity of incunabula
and artworks. For instance it is possible to determine
the artist and creation date of an artwork by discovering
identical pieces of paper. Assume e.g. two etchings of
Rembrandt. The one has been printed in 1648 and the other
has an unknown date. However, since both have been
made on the same paper, it is reasonable to suppose that
also the other one has been made in 1648. The reason is
that in the 16 th -18 th century paper was sold in stocks of paper
sheets coming from the same paper mill and mould,
which implies an identical paper structure and watermark.
For that very reason watermarks and paper structures are
collected all over the world by national libraries, archives,
museums and art historical institutes, and watermark catalogues
are published everywhere.
Until now most collections of watermarks are in the form
of line-drawings, rubbings, backlight and x-ray imagery. A
part of them are now digitized. In the Bernstein project one
tries to combine these digital databases to one large virtual
repository of watermarks. As a matter of fact this will be a
very powerful help for experts in the field of (art) history
and incunabula. However, the generation of all these digital
databases is an enormous task if it should be done manually.
And furthermore, the question is: when this large database
is available how to find the appropriate information
searched for? At the Delft University of Technology, research
is performed how far the usage of computers can
assist in these complex tasks. In this paper some examples
are given.
Watermark detection
Before a computer can handle imagery of watermarks all
the line-drawings, rubbings, backlight and x-ray images
should be in a digital form. In practice this means that each
picture element (the so-called pixel) should be represented
by a number, in general between 0 and 255, representing
the grayscale values of the various picture elements. At this
moment most of the new watermark images are digitized
directly, since most of the present image generation techniques
are digital. In case of printed watermarks and ‘analogue’
photographs they should be digitized first. Until now
watermark extraction was primarily be done manually by
using transparencies and tracing off with as a result a linedrawing.
In fact it simple, but taking into account the large
amount of watermarks a tedious drudgery. Furthermore, as
a matter of fact the final result is not exact and differs
sometimes a little bit from the original real watermark.
However, for a computer watermark extraction is a complex
task (with the exception of binary imagery which only has
black and white pixels). Considering the X-ray images they
are in general very noisy. This holds especially for 16 th and
17 th century paper. Ill. 10 gives an example; even for the expert
it is difficult to determine which points belong to the
watermark and which ones do not. And this holds the more
for the computer since it has only a huge amount of numbers,
representing the image, and in which it should detect
the watermark pixels.
Our goal is the development of a method which could
detect automatically as many watermarks as possible without
any user interaction. The basic idea is that watermarks
are formed by lines and have specific properties. In the
present case we considered five properties:
a) the line profile: the one-dimensional representation of
the section in terms of intensity,
b) the line contrast: the contrast difference with the background,
c) the line width,
d) the spatial connectivity: lines exist from connected
points,
e) and the line length.
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