The Promise and Perils of Near-Regular Texture

Authors:
Yanxi Liu;Yanghai Tsin;Wen-Chieh Lin
Affiliations:
The Robotics Institute, Carnegie Mellon University, Pittsburgh, USA;The Robotics Institute, Carnegie Mellon University, Pittsburgh, USA;The Robotics Institute, Carnegie Mellon University, Pittsburgh, USA
Venue:
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
Year:
2005

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Abstract

Motivated by the low structural fidelity for near-regular textures in current texture synthesis algorithms, we propose and implement an alternative texture synthesis method for near-regular texture. We view such textures as statistical departures from regular patterns and argue that a thorough understanding of their structures in terms of their translation symmetries can enhance existing methods of texture synthesis. We demonstrate the perils of texture synthesis for near-regular texture and the promise of faithfully preserving the regularity as well as the randomness in a near-regular texture sample.