Image Processing for Optical Metrology

Abstract

Optical measurements offer the desirable characteristics of being noninvasive and nondestructive techniques that are able to analyze in real time objects and phenomena in a remote sense. Science areas that involve optical characterization include physics, biology, chemistry and varied fields of engineering. The use of digital cameras to record objects or a specific phenomenon permits the exploitation of the potential of that the associated images can be processed to determine one or several parameter or characteristics of what is being recorded. These images need to be processed and securely there will be a model associated with the optical metrology that will provide an insight or a comprehensive understanding of the image being analyzed. Matlab® is the suitable platform to implement image processing algorithms due to its ability to perform the whole processing techniques and procedures to analyze and image. At the same time it provides a flexible and a fast programming language for user constructing algorithms. In the present chapter we provide some fundamentals about image acquisition, filtering and processing, and some applications. Some applications are well-know techniques while others offer the state of the art in the field under study. All authors agree that Matlab® is a powerful tool for image processing and optical metrology. All algorithms and/or sentences used in this chapter are made in such manner so that they work in the Matlab® R2007b platform or superior. Matlab® is a trade mark of Mathworks Inc., from here on we will refer it as Matlab only. Also the Matlab functions and parameters used along the chapter are typed in italics and in apostrophes, respectively. Algorithms in present chapter are presented in two formats depending on the algorithm extension: 1) Image titles and/or figure captions for low algorithms extension; 2) Subsection ends for larger algorithms.