A low-cost sensor platform (MORES Sensor) was combined with a microcontroller to build up an embedded solution
which e.g. allows for a small hand-held Color Estimation System for blind people. The color sensor used here measures
the intensity response of a surface caused by radiation with a specific wavelength in the range of visible light. This
radiation is realized by means of three LEDs, red, green, and blue, so that the response intensity values create an R'G'B'
color space, which differs from the standardized RGB color space due to the wavelengths of the LEDs. By adjusting the
measured response of the LEDs to the known spectral response of the individual color panels of the Macbeth Color
Checker Chart (MCCC) a corresponding set of coordinates can be constructed for this particular R'G'B' color space.
Owing to this approach, it is possible to obtain reasonable color classification results, which can be compared to those of
far more complex and expensive systems. The verification of the results was done by using the standardized MCCC
together with commercial vision solutions (RGB camera in combination with PC software). Moreover, some comparison
tests also prove the practicality of the here described low-cost color sensor solution.
The use of surface acoustic wave (SAW) devices is a widely adopted method for implementing unique identification tags that operate completely passively and can be interrogated wirelessly. Interrogation can be done in the time- or frequency-domain, where in the latter case bandwidth is a restraining factor. Conventional signal evaluation is based on the fast Fourier transformation (FFT), which suffers from resolution limitations. Modern model-based frequency estimators have been investigated for SAW ID-tag identification. A state-space algorithm is applied to measured data and compared to FFT evaluation results.