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ABSTRACT
The knowledge of the size of populations of waterfowls
in North America is necessary to properly manage this renew
able resource. The most common methods of counting waterfowls
during the census are by visual means from low flying aircraft
or from aerial photographs of large bird concentrations. While
the first method is inaccurate, the second one is time consuming
and also presents problems of classification where a large
number of waterfowl or a mixture of several species, age
and sex groups occur on the photographs. To overcome these
difficulties a research program was initiated using pattern
recognition techniques in the census. This research covers
three interconnected subject areas: experimental aerial
photography, digitization of photographic images through
micro-densitometry, and pattern recognition.
Experimental aerial photography of greater snow geese,
eider ducks, and of diving ducks was carried out using
several films exposed at various scales to determine the
best photographic media for the densitometry and pattern
recognition. The obtained aerial photographic images were
digitized using an automatic scanning micro-densitometer.
Density and image shape patterns were established for the
above species and for various sub-groups within the species.
A FORTRAN program was developed to count black ducks and
snow geese for one unit record of digitized image. Work
is in progress to expand this program to accommodate larger
records and complex patterns.
Results indicate that normal and false color photography
is superior to black and white in all respects. ’ The three
different layers of the color film can be analysed separately
by the densitometer. This yields optimum separation of
desired groups.
nd.