This paper introduces a new comprehensive procedure for both geometric and colour calibration of structured light system. In order to perform both geometric and colour calibration procedure, a new calibration artifact is proposed. The intrinsic and extrinsic parameters of projector and camera are estimated by using an extended pinhole camera model with a tangential and radial distortion. Camera image plane coordinates are obtained by extracting features from images of a calibration artifact. Projector image plane coordinates are calculated on the basis of continuous phase maps obtained from a fringe pattern phase reconstruction procedure. In order to stereo calibrate camera-projector system, pairs of corresponding image plane points are calculated with subpixel accuracy. In addition, one of three pattern views is used in colour calibration. RGB values of a colour field pattern detected by camera and their reference values are compared. This comparison leads to derivation of a colour transformation matrix. The performance of the proposed method is tested by measuring plane, sphere and distance reference. Also 360 degrees complex object 3D model from a set of measurements is obtained. Residual mean errors for all tests performed are calculated.

A metamaterial absorber (MA) based sensor is designed and analysed for various important applications including pressure, temperature, density, and humidity sensing. Material parameters, as well as equivalent circuit model have been extracted and explained. After obtaining a perfect absorption (PA) at around 6.46 GHz and 7.68 GHz, surface current distributions at resonance points have been explained. Since bandwidth and applicability to different sensor applications are important for metamaterial sensor applications, we have realized distinctive sensor demonstrations for pressure, temperature, moisture content and density and the obtained results have been compared with the current literature. The proposed structure uses the changes on the overall system resonance frequency which is caused by the sensor layer’s dielectric constant that varies depending on the electromagnetic behaviour of the sample placed in. This model can be adapted to be used in sensor applications including industrial, medical and agricultural products.