Spot detection and pattern matching for individual whale shark identification

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Authors
Brennan, Nicholas
Issue Date
2017-12
Type
Electronic thesis
Thesis
Language
ENG
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Computer science
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Abstract
Photographic identification of individual animals is a vital tool for conservation efforts. We produce an algorithm to match spot patterns in whale sharks by segmenting a portion of the animal, detecting the locations of its spots, and matching them between images. We make use of convolutional neural networks to perform segmentation and spot detection, and a modification of the RANSAC algorithm for point matching. Our results show that we are able to accurately extract spot locations from the segmented images. However, segmentation is not reliable enough to replace the need for human interaction, and our matching algorithm did not produce effective results.
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December 2017
School of Science
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Rensselaer Polytechnic Institute, Troy, NY
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