Application of Red, Green, and Blue Color Channels in 3D Shape Measurement

Application of Red, Green, and Blue Color Channels in 3D Shape Measurement

Zonghua Zhang (Hebei University of Technology, China)
DOI: 10.4018/978-1-4666-0113-0.ch011
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Abstract

Optical full-field measurement techniques have been widely studied in academia and applied to many actual fields of automated inspection, reverse engineering, cosmetic surgery, and so on. With the advent of color CCD cameras and DMD (Digital Micromirror Device) based color DLP (Digital Light Processing) projectors, their major red, green, and blue channels have been used as a carrier to code fringe patterns. Since three fringe patterns can be simultaneously projected and captured at one shot, the acquisition time reduces to 1/3 of the value by the gray fringe pattern projection. This chapter will introduce two kinds of applications of red, green, and blue as a carrier: 1) modulation and demodulation method of coding sinusoidal fringe patterns into RGB channels of a composite color image; and 2) modulation and demodulation method of coding sinusoidal and binary fringe patterns into RGB channels of multiple composite color images. Experiments on testing the two kinds of applications were carried out by measuring the shape of objects’ surface. The results confirm that red, green, and blue channels can be used as a carrier to reduce the acquisition time.
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Introduction

Optical full-field measurement techniques, especially phase-based fringe projection, have been widely studied and applied to fields of automated inspection, reverse engineering, cosmetic surgery and so on owing to the advantages of non-contact operation, fast acquisition, high precision and automatic processing (Chen, Brown & Song, 2000; Petrov, Talapov, Robertson, Lebedev, Zhilyaev & Polonskiy, 1998; Blais, 2004). With the increasing demands of the accuracy, speed and surface properties, such as color texture and shiny surface, new measuring techniques and methods have emerged to satisfy with these requirements. In fringe projection techniques, unambiguous absolute phase calculation of objects having surface discontinuities and/or spatially isolated surfaces is one of the most challenging problems (Gorthi & Rastogi, 2010). Several strategies, including temporal phase unwrapping (Saldner & Huntley, 1997), optimum multi-frequency selection method (Towers, Towers & Jones, 2005), and spatiotemporal phase unwrapping (Zhang, Lalor & Burton, 1999), have been developed to solve such problems of the absolute phase discontinuities. The temporal phase unwrapping technique (Saldner & Huntley, 1997) used a sequence of binary fringe patterns with the fringe numbers of geometric series to determine the fringe order of each sinusoidal fringe pattern, so it need to capture more images to calculate the absolute phase map. The optimum multi-frequency selection method (Towers, Towers & Jones, 2005) greatly reduced the required images by using a geometric series of synthetic wavelengths. However, these methods need to capture more multiple fringe pattern images, so that the acquisition time is much longer than spatial phase unwrapping methods. For fast capturing 3D shape data or measuring dynamic objects, multiple fringe pattern images projection and acquisition techniques are not an ideal choice.

With the advent of color CCD cameras and DMD (Digital Micromirror Device) based DLP (Digital Light Processing) projectors, the major color channels (mostly red, green and blue) have been used to facilitate identification as spatial identifier (Wong, Niu & He, 2005; Koninckx & Gool, 2006) or to code fringe patterns as a carrier (Hausler & Ritter, 1993; Huang, Hu, Jin & Chiang, 1999; Skydan, Lalor & Burton, 2002; Zhang, Towers & Towers, 2006; Karpinsky & Zhang, 2010). All these methods use color information to generate different structured color patterns and then projected them onto a measured object surface. For the techniques of using color channels as identifier (Wong, Niu & He, 2005; Koninckx & Gool, 2006), the color patterns should have a minimum size to be easily identified, so that the measured data has small resolution. In order to increase resolution, the structured color patterns should contain enough entries. However, the depth resolution reported to date does not compare with that from phase measurement of projected sinusoidal fringe patterns. Processing errors can also be introduced due to hue variations of the object surface.

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