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    Spot detection and pattern matching for individual whale shark identification

    Author
    Brennan, Nicholas
    View/Open
    178746_Brennan_rpi_0185N_11191.pdf (6.514Mb)
    Other Contributors
    Stewart, Charles V.; Stewart, Charles V.; Cutler, Barbara M.; Gittens, Alex;
    Date Issued
    2017-12
    Subject
    Computer science
    Degree
    MS;
    Terms of Use
    This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.;
    Metadata
    Show full item record
    URI
    https://hdl.handle.net/20.500.13015/2110
    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.;
    Description
    December 2017; School of Science
    Department
    Dept. of Computer Science;
    Publisher
    Rensselaer Polytechnic Institute, Troy, NY
    Relationships
    Rensselaer Theses and Dissertations Online Collection;
    Access
    Restricted to current Rensselaer faculty, staff and students. Access inquiries may be directed to the Rensselaer Libraries.;
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