Surface Measurement Techniques in Machine Vision: Operation, Applications, and Trends

Background

Surface measurement systems in its common definition is the possibility of a machine (by sensing means and computer mathematic processing consecutively) to obtain information about surrounding environment for further analytical treatment. According to the common definition, any complete surface measurement system or machine vision system is a combination of two components: technical means (hardware) and information processing mathematics and algorithm (software), (Rivas-Lopez, Sergiyenko, & Tyrsa, 2008).

Surface measurement systems are related to many fields, techniques developed from different areas are used for recovering information of objects like image processing, where its algorithms are useful in early stages of surface measurement systems, curve and surface representations and other techniques are used from computer graphics, also, computer graphics uses many techniques from surface measurement systems to enter models into the computer for creating realistic images. Other area is pattern recognition, where many statistical techniques have been developed for classification of patterns, artificial intelligence is used to analyze scenes by computing a symbolic representation of the scene contents after the information has been processed to obtain features (Cuevas-Jimenez, 2006).

In this chapter a compilation of non-contact measurement techniques are presented, they are divided according to their mode of operation, also, the working principle, basic equations, system implementation and future trends are shown and how all of these techniques can be implemented together to improve the performance of the vision system.