  At least two software packages---DARWIN, Eckerd College, and FinScan, Texas
A&M---exist to facilitate the identification of cetaceans---whales, dolphins,
porpoises---based upon the naturally occurring features along the edges of
their dorsal fins. Such identification is useful for biological studies of
population, social interaction, migration, etc. The process whereby fin
outlines are extracted in current fin-recognition software packages is manually
intensive and represents a major user input bottleneck: it is both time
consuming and visually fatiguing. This research aims to develop automated
methods (employing unsupervised thresholding and morphological processing
techniques) to extract cetacean dorsal fin outlines from digital photographs
thereby reducing manual user input. Ideally, automatic outline generation will
improve the overall user experience and improve the ability of the software to
correctly identify cetaceans. Various transformations from color to gray space
were examined to determine which produced a grayscale image in which a suitable
threshold could be easily identified. To assist with unsupervised thresholding,
a new metric was developed to evaluate the jaggedness of figures ("pixelarity")
in an image after thresholding. The metric indicates how cleanly a threshold
segments background and foreground elements and hence provides a good measure
of the quality of a given threshold. This research results in successful
extractions in roughly 93% of images, and significantly reduces user-input
time.
