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

Ill. 12: Watermark detection in a very noisy image
tion. All these elements need first to be identified in order to
properly isolate the watermark. The main problem for the
computer is to decide what belongs to the watermark and
what not.
In our method first groups of connected black pixels are
detected, the so-called Blobs (binary large objects). E.g. a
window in the castle of Ill. 13 is a blob, the group of laid
lines is a blob et cetera. Thereafter all these blobs are studied
by the computer by looking to their size, their mutual
distances et cetera. Specific properties like many lines with
a certain length are for the computer an indication that it
probably has to do with a blob with laid lines. This blob is
then removed. In the same way blobs with text can be detected
and removed et cetera. The final result will be the
isolated digital watermark without all its additional information.
In experiments the performance was 84%. Of course,
sometimes it is going wrong; e.g. a chain line is detected as
a part of the watermark.
With respect to the printed collections we have similar
problems. The printed Piccard (see Chapter V) consists of
45,000 watermarks, represented in 17 volumes. As a matter
of fact these watermarks should also be in the digital
database. All the pages are now scanned, but since there
are a number of watermarks on each page, further digital
processing of the individual is impossible without a method
that first isolates the individual watermarks. Of course this
can be done manually (e.g. by using Photoshop), but for
45,000 watermarks this is a time consuming job. Also here
the computer can assist. First the number of watermarks is
determined by locating the numbers of the watermarks in a
way as done for Piccard-Online and then counting them.
And since these numbers are always below the watermark
the positions of the watermark can be determined and finally
the watermark which then can be isolated. In about
88% of the cases this goes correct. In the other cases the
user has to correct the result manually. But still this method
saves much time (Ill. 14).
Matching and retrieval of watermarks
Once the digital watermarks have been extracted they can
be stored in a database and used for retrieval purposes. Assume
you have an artwork with a watermark and want to
Ill. 13: Watermark with additional information, from the Piccard-
Online database
know whether there is an identical watermark in Piccard.
For the expert it is a time consuming task, even if he should
only compare it with watermarks of the same category.
Their amount can be large and the differences small. For
the human eye it is rather difficult to decide whether two
watermarks are identical. A very simple method is the following.
The computer puts a grid on the watermark, consisting
of blocks of a certain size. Within each blocks the
number of pixels belonging to the watermark are counted.
By doing this for all blocks a series of numbers is obtained,
a so-called vector. And this is again done for all watermarks.
By comparing the series of numbers – which goes
very fast – identical or nearly similar watermarks can easily
be detected. From experiments with the Piccard database it
works out for 91% of the cases.
Chain lines and laid lines
Although according to the experts watermarks are the most
important paper feature in order to discover identical pieces
of paper, they are not always present in a piece of paper. If
a sheet of paper with one watermark is divided in smaller
pieces, e.g. in the case of making prints of an etching plate,
in general just one piece of paper contains a watermark,
the other ones do not. For that very reason one also consid-
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