Ph.D. thesis: Stefano Padilla
Mathematical Models for Perceived Roughness of Three-Dimensional Surface Textures
Heriot-Watt University, 2008.
This thesis reports and discusses results from a new methodology for investigating the visually perceived properties of surfaces; by doing so, it also discovers a measurement or estimator for perceived roughness of 1 / F &beta noise surfaces.
Advanced computer graphics were used to model natural looking surfaces (1 / F &beta noise surfaces). These were generated and animated in real-time to enable observers to manipulate dynamically the parameters of the rendered surfaces. A method of adjustment was then employed to investigate the effects of changing the parameters on perceived roughness. From psychophysical experiments, it was found that the two most important parameters related to perceived roughness were the magnitude roll-off factor (&beta) and RMS height (&sigma) for this kind of surfaces.
From the results of various extra experiments, an estimation method for perceived roughness was developed; this was inspired by common frequency-channel models. The final optimized model or estimator for perceived roughness in 1 / F &beta noise surfaces found was based on a FRF model. In this estimator, the first filter has a shape similar to a gaussian function and the RF part is a simple variance estimator. By comparing the results of the estimator with the observed data, it is possible to conclude that the estimator accurately represents perceived roughness for 1 / F &beta noise surfaces.
Table of contents
Chapter 1 Introduction
Chapter 2 Roughness and surfaces
Chapter 3 A general methodology
Chapter 4 Modelling the stimuli
Chapter 5 Experimental setup
Chapter 6 Roughness in 1 / F &beta surfaces
Chapter 7 A model based on the human vision
Chapter 8 Testing the models using narrow-band sprectra surfaces
Chapter 9 Scaling the proposed model
Chapter 10 Summary and conclusions