Abstract
The bidirectional reflectance-distribution function (BRDF) is a characteristic property of a reflecting surface and describes the reflectance in terms of the directions of the incident and the reflected light. Among other fields of application, BRDF measurements are used for automated optical inspection in production processes or in computer graphics where virtual surfaces are visualized under different artificial lighting conditions.
A device to measure the BRDF is referred to as gonioreflectometer. The camera-based gonioreflectometer (CBGR) presented in this thesis uses one of nine available LEDs to illuminate the specimen and a conventional CCD-camera to measure the radiance of the reflected light. Four degrees of freedom are required to adjust the directions of the incident and the reflected light. These are provided by a construction with four mechanical axes, allowing flat specimens with weights of up to 3kg. Despite the readily available and quite inexpensive components in use, sophisticated calibration procedures lead to measurements with low uncertainty. A custom integrating sphere is applied for the radiometric calibration of the camera. The spectra and the radiant intensity distributions of the LEDs are measured. Moreover, the geometric parameters of the complete setup are estimated by means of acquisition of two specially designed calibration targets. The exact knowledge of the geometry enables, among other things, the measurement of the spatially varying BRDF (SVBRDF) without the need for dedicated registration marks on the specimen.
The performance of the CBGR is evaluated by measurements of a diffuse reflection standard and a mirror. The measurements of the reflection standard are also compared to measurement results provided by the manufacturer of the standard. Finally, the measured SVBRDF of a banknote is shown.
Translated title of the contribution | Design, Calibration and Evaluation of a Camera-based Gonioreflectometer |
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Original language | German (Austria) |
Publication status | Published - Mar 2018 |
Fields of science
- 102003 Image processing
- 202022 Information technology
- 202027 Mechatronics
- 202037 Signal processing
- 103021 Optics
JKU Focus areas
- Computation in Informatics and Mathematics
- Mechatronics and Information Processing
- Engineering and Natural Sciences (in general)