Author

Manil Maskey

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.

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