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View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by DigitalCommons@USU Utah State UnivUtah State University ersity DigitalCommons@USU DigitalCommons@USU All Graduate Theses and Dissertations Graduate Studies 5-2009 A Computational A Computational GeometrGeometry Appry Approach toach to Digital Image o Digital Image ContContour our ExtrExtraction action Pedro J. Tejada Utah State University Follow this and additional works at: https://digitalcommons.usu.edu/etd Part of the Computer Sciences Commons Recommended Citation Recommended Citation Tejada, Pedro J., "A Computational Geometry Approach to Digital Image Contour Extraction" (2009). All Graduate Theses and Dissertations. 422. https://digitalcommons.usu.edu/etd/422 This Thesis is brought to you for free and open access by the Graduate Studies at DigitalCommons@USU. It has been accepted for inclusion in All Graduate Theses and Dissertations by an authorized administrator of DigitalCommons@USU. For more information, please contact digitalcommons@usu.edu. ACOMPUTATIONALGEOMETRYAPPROACHTO DIGITAL IMAGE CONTOUR EXTRACTION by Pedro J. Tejada Athesis submitted in partial fulfillment of the requirements for the degree of MASTEROFSCIENCE in Computer Science Approved: Dr. Minghui Jiang Dr. Xiaojun Qi Major Professor Committee Member Dr. Nicholas Flann Dr. Byron R. Burnham Committee Member Dean of Graduate Studies UTAHSTATEUNIVERSITY Logan, Utah 2009 ii c Copyright Pedro J. Tejada 2009 All Rights Reserved iii Abstract AComputational Geometry Approach to Digital Image Contour Extraction by Pedro J. Tejada, Master of Science Utah State University, 2009 Major Professor: Dr. Minghui Jiang Department: Computer Science Wepresentamethodforextracting contours fromdigital images, usingtechniques from computational geometry. Our approach is different from traditional pixel-based methods in image processing. Instead of working directly with pixels, we extract a set of oriented feature points from the input digital images, then apply classical geometric techniques, such as clustering, linking, and simplification, to find contours among these points. Experiments on synthetic and natural images show that our method can effectively extract contours, even from images with considerable noise; moreover, the extracted contours have a very compact representation. (176 pages)
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