In-process surface profile assessment of rotary machined timber using a dynamic photometric stereo technique

Machining operations have advanced in speed and there is an increasing demand for higher quality surface finish. It is therefore necessary to develop real-time surface inspection techniques which will provide sensory information for controlling the machining processes. This paper describes a practical method for real-time analysis of planed wood using the photometric stereo technique. Earlier research has shown that the technique is very effective in assessing surface waviness on static wood samples. In this paper, the photometric stereo method is extended to real industrial applications where samples are subjected to rapid movements. Surface profiles extracted from the dynamic photometric stereo method are compared with those from the static measurements and the results show that there is a high correlation between the two methods

Efficient photometric stereo on glossy surfaces with wide specular lobes.

Chung, Hin Shun.Thesis (M.Phil.)--Chinese University of Hong Kong, 2008.Includes bibliographical references (leaves 40-43).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Lambertian photometric stereo --- p.1Chapter 1.2 --- Non-Lambertian photometric stereo --- p.3Chapter 1.3 --- Large specular lobe problems --- p.4Chapter 2 --- Related Work --- p.9Chapter 2.1 --- Lambertian photometric stereo --- p.9Chapter 2.2 --- Non-Lambertian photometric stereo --- p.9Chapter 2.2.1 --- Analytic models to reconstruct non-Lambertian surface --- p.9Chapter 2.2.2 --- Reference object based --- p.10Chapter 2.2.3 --- Highlight removal before shape reconstruction --- p.11Chapter 2.2.4 --- Polarization based method --- p.12Chapter 2.2.5 --- Specularity fitting method --- p.12Chapter 2.2.6 --- Photometric stereo with shadow --- p.12Chapter 3 --- Our System --- p.13Chapter 3.1 --- Estimation of global parameters --- p.14Chapter 3.1.1 --- Shadow separation --- p.16Chapter 3.1.2 --- Separation edges of shadow and edges of foreground object --- p.16Chapter 3.1.3 --- Normal estimation using shadow boundary --- p.20Chapter 3.1.4 --- Global parameter estimation and refinement --- p.22Chapter 3.2 --- Surface shape and texture reconstruction --- p.24Chapter 3.3 --- Single material results --- p.25Chapter 4 --- Comparison between Our Method and Direct Specularity Fitting Method --- p.29Chapter 4.1 --- Summary of direct specularity fitting method [9] --- p.29Chapter 4.2 --- Comparison results --- p.31Chapter 5 --- Reconstructing Multiple-Material Surfaces --- p.33Chapter 5.1 --- Multiple material results --- p.34Chapter 6 --- Conclusion --- p.38Bibliography --- p.39Chapter A --- Proof of Surface Normal Projecting to Gradient of Cast Shadow Boundary --- p.4