A Practical Device for Measuring the Luminance Distribution

Abstract

Various applications in building lighting such as automated daylight systems, dynamic lighting control systems, lighting simulations, and glare analyzes can be optimized using information on the actual luminance distributions of the surroundings. Currently, commercially available luminance distribution measurement devices are often not suitable for these kind of applications or simply too expensive for broad application. This paper describes the development of a practical and autonomous luminance distribution measurement device based on a credit cardsized single-board computer and a camera system. The luminance distribution was determined by capturing High Dynamic Range images and translating the RGB information to the CIE XYZ color space. The High Dynamic Range technology was essential to accurately capture the data needed to calculate the luminance distribution because it allows to capture luminance ranges occurring in real scenarios. The measurement results were represented in accordance with established methods in the field of daylighting. Measurements showed that the accuracy of the luminance distribution measurement device ranged from 5% to 20% (worst case) which was deemed acceptable for practical measurements and broad applications in the building realm.

Ceiling-Based Luminance Measurements: A Feasible Solution?

“…The B&A plots of Figure 4 show a distinct pattern with over-and underestimated luminance values. This effect can be caused by the two image sequences that were applied for darker and brighter conditions, respectively (Kruisselbrink, Aries and Rosemann, 2017). It is very likely, that the transition in the B&A plots coincide with the transition in image sequences as it is not caused by the absolute luminance (75 cd/m 2 to 150 cd/m 2 ).…”

“…The measurements were conducted with 3 identical devices that were able to measure the luminance distribution autonomously and with a practical accuracy, similar to the device described by Kruisselbrink, Aries and Rosemann, 2017. The devices consist of a single-board computer (Raspberry Pi 3 Model B), a camera (Raspberry Pi Camera Board version 2), a fisheye lens and custom software providing an equisolid-angle luminance projection on the imaging sensor with a spatial resolution of 2130 pixels × 1600 pixels.…”

“…Previously, the luminance distribution was measured by spot luminance meters, which was a tedious and imprecise method due to rapid changes in the luminous environment. However, current High Dynamic Range (HDR) imaging technology has enabled the scientific community to measure the luminance distribution using image-based systems (so-called luminance cameras) (Inanici, 2006;Kruisselbrink, Aries and Rosemann, 2017). Generally, the luminance is calculated based on the floating point Red-Green-Blue (RGB) pixel values of the HDR image, which is captured using sequential exposure bracketing.…”

Preferred luminance distributions in open-plan offices in relation to time-of-day and subjective alertness

“…The task luminance was not included as a DV because participants were not allowed to dim the task level; hence, the luminance in this area remained relatively constant. After the experiment, participants' settings were retrieved and the resulting scenes were photographed with Bee-Eye, a luminance distribution measurement device developed by Kruisselbrink et al (2017). The resulting pictures were automatically combined in a high-dynamic-range image; we used the Hdrscope program developed by Inanici and Heerwagen (2012) to obtain the median luminances in the three areas; the use of mask images ensured consistency across the analyses (see Fig.…”

Scatterometer and Intensity Distribution Meter With Screen Image Synthesis

“…Therefore, a fast and versatile measuring instrument is urgently required. In many fields, imaging measurement technology has been applied to improve the intensity distribution measurement and the speed of bidirectional scattering distribution function (BSDF) meters [21][22][23][24][25][26][27][28][29][30][31][32][33]. Ward presented an elegant system using a hemisphere as a projection surface and a fish-eye lens for capturing images [34,35].…”