Tackling Heterogeneous Color Registration: Binning Color Sensors

Abstract

Intelligent systems for interior lighting strive to balance economical, ecological, and health-related needs. For this purpose, they rely on sensors to assess and respond to the current room conditions. With an augmented demand for more dedicated control, the number of sensors used in parallel increases considerably. In this context, the present work focuses on optical sensors with three spectral channels used to capture color-related information of the illumination conditions such as their chromaticities and correlated color temperatures. One major drawback of these devices, in particular with regard to intelligent lighting control, is that even same-type color sensors show production related differences in their color registration. Standard methods for color correction are either impractical for large-scale production or they result in large colorimetric errors. Therefore, this article shows the feasibility of a novel sensor binning approach using the sensor responses to a single white light source for cluster assignment. A cluster specific color correction is shown to significantly reduce the registered color differences for a selection of test stimuli to values in the range of 0.003–0.008 Δu′v′, which enables the wide use of such sensors in practice and, at the same time, requires minimal additional effort in sensor commissioning.

LED Degradation Monitoring Using a Multi-Channel Spectral Sensor

“…These sensitivities were determined using an MSH 300 monochromator setup (Quantum Design GmbH, Darmstadt, Germany) with a 300 W xenon arc lamp from 370 nm to 780 nm in steps of ∆λ=1 nm, with probe stimuli of approximately 3 nm full-width at half-maximum (FWHM), see e.g. Myland et al [41] or Trinh et al [26] for further details.…”

“…The aforementioned Wiener filter approach requires knowledge of the spectral sensitivities of the sensor, which can only be accurately determined through elaborated procedures using expensive measurement techniques [41]. Although there are methods in the literature, as mentioned earlier, to estimate the sensitivities of a sensor from more practical setups, it requires to carefully consider how the errors in this sensitivity estimations would affect the reconstruction quality.…”

The Use of Artificial Neural Networks (ANN) in the Chayote Chips Dough Mixer

“…This sensor module's digital inputs and outputs enable a direct connection to a microcontroller or other logic circuit [12]. We are able to determine the intensity of each color by using various filters [13]. By giving the control pins S2 and S3 the logical values LOW and HIGH, the filter is selected…”

Processing RGB Color Sensors for Measuring the Circadian Stimulus of Artificial and Daylight Light Sources

“…In experimental test settings, these kinds of data can be generated straightforwardly by using expensive spectroradiometers or other sophisticated measurement devices. However, in view of large-scale applications, where such "laboratory" devices are not an option due to budgetary constraints, the use of simple and inexpensive RGB color sensors to be applied for this purpose appears to be quite promising [37][38][39][40][41], yet requires a suitable processing of the sensor readouts in order to obtain meaningful measures that can eventually be used as the input for an adequate lighting control [42].…”