Date of Award
2019
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Computer Science
Committee Chair
Timothy S Newman
Committee Member
Heggere Ranganath
Committee Member
Sara Graves
Committee Member
Ramazan Aygun
Committee Member
Udaysankar Nair
Subject(s)
Computer vision, Visualization
Abstract
This dissertation focuses on three aspects of directional textures. The first aspect is the development of a new directional texture-based visualization technique to address challenges in visualizing multivariate data in a single display. The technique uses a multi level Markov Random Field-based texture synthesis to progressively generate a visualization that encodes data variables using various texture features, especially texture direction. Since texture directionality has not been used extensively in visualization, this technique provides a new visual cue to display additional data variable in a single display. Evaluations of the new texture-based visualization technique are also presented. The second aspect is the development of a new texture directionality measure to determine directional status of textures. The new texture directionality measure considers both local and global characteristics of textures. A comprehensive comparison study of the new measure with existing measures is also presented. The comparison is the first such study that considers all textures from the Brodatz texture database. The third aspect is applications of the new texture directionality measure to several classification problems.
Recommended Citation
Maskey, Manil, "Measuring and evaluating directional textures and using them in visual discovery" (2019). Dissertations. 175.
https://louis.uah.edu/uah-dissertations/175