Abstract—Analysis of shoreline detection has importance in
many investigations undertaken by coastal zone and coastal
management studies. These studies require tracking changes in
shorelines to reach many objectives such as detecting erosion
and land mass movements, discriminating land and sea and etc.
At the same time shorelines are important features to display
dynamic nature of Earth’s surface.
In this paper a novel shoreline extraction method and use of
fractals as a performance evaluator are proposed. As a first
step of shore line extraction, blurring is done on shoreline image
to reduce noise. Then variance map calculation and
thresholding are applied. In second stage, a series of
morphological binary image processing techniques are
performed. After user feedback, boundary of the resulting
connected component is extracted. Performance evaluation of
the proposed method is done by using fractal values. Evaluation
is done by matching calculating fractal values of extracted lines
and fractal values of handrawn shorelines. A high correlation
has been seen between fractal values of computed and
handrawn shorelines.Considering the ability of fractal
geometry to express natural entities, fractal dimension is
contributed as a performance metric.
Index Terms—Shoreline extraction, fractal, performance
evaluation, image processing.
The authors are with the Computer Engineering Department of Hacettepe
University, Ankara, Turkey (e-mail: sinanonur @hacettepe.edu.tr,
aliseydi.keceli@hacettepe. edu. tr, ebru@hacettepe.edu.tr).
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Cite:Sinan O. Altinuc, Ali S. Keceli, and Ebru A. Sezer, "Semi-Automated Shoreline Extraction in Satellite Imagery and Usage of Fractals as Performance Evaluator," International Journal of Computer Theory and Engineering vol. 6, no. 2, pp. 102-106, 2014.
