Abstract

Textures are the most important element for simulating real-world scenes and providing realistic and immersive sensations in many applications. Procedural textures can simulate a broad variety of surface textures, which is helpful for the design and development of new sensors. Procedural texture generation is the process of creating textures using mathematical models. The input to these models can be a set of parameters, random values generated by noise functions, or existing texture images, which may be further processed or combined to generate new textures. Many methods for procedural texture generation have been proposed, but there has been no comprehensive survey or comparison of them yet. In this paper, we present a review of different procedural texture generation methods, according to the characteristics of the generated textures. We divide the different generation methods into two categories: structured texture and unstructured texture generation methods. Example textures are generated using these methods with varying parameter values. Furthermore, we survey post-processing methods based on the filtering and combination of different generation models. We also present a taxonomy of different models, according to the mathematical functions and texture samples they can produce. Finally, a psychophysical experiment is designed to identify the perceptual features of the example textures. Finally, an analysis of the results illustrates the strengths and weaknesses of these methods.

Highlights

  • Texture, as a basic property of the surface of an object, is an extremely important feature for describing and identifying objects which exist widely in nature

  • Procedural models are essential for providing provide realistic surface details in simulation or animation systems [3]. They have been widely used in many research and application fields involved with cyber-physical systems (CPS), such as Virtual Reality and Augmented Reality

  • We briefly introduce each method together with texture examples with varied appearances, which the method can produce by changing the input parameters

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Summary

Introduction

As a basic property of the surface of an object, is an extremely important feature for describing and identifying objects which exist widely in nature. Sensors 2020, 20, 1135 together with sensors to provide integrated systems In this context, a broad variety of textures that can simulate real surfaces are helpful in the design and development of new sensors. Procedural models are essential for providing provide realistic surface details in simulation or animation systems [3]. They have been widely used in many research and application fields involved with cyber-physical systems (CPS), such as Virtual Reality and Augmented Reality. Such systems require a large amount of high-resolution textures to provide an immersive sensation for users. Such high-resolution textures may even be required to be generated in real-time [4,5]

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