Color sensors

A ICO p-i-n-i-pflCOIp-i-nlmci.d stack has been designed as a three-color sensor [643,644], An extra contact is made to the middle TCO. With appropriate bandgaps the peak detection is at 450, 530, and 635 nm for the blue, green, and red, respectively. 

Vogeley, L., O. A. Sineshchekov et al. (2004). Anabaena sensory rhodopsin A photochromic color sensor at 2.0 angstrom. Science 306(5700) 1390-1393. 

This can be realized with modem sensors such as infrared thermopiles, thermopile arrays, microspectrometers and color sensors, several types of humidity sensors, artificial noses and multi-gas sensors. 

Some of these functions could be monitored with improved sensors, instruments and microsystems, like microspectrometers and color sensors, thermopiles, artificial noses, etc. Also some dosing and mixing functions (e. g. of herbs and spices) could be controlled by microfluidic systems. 

Cox, E. R. Jones, B. E. Fiber optic color sensors based on Fabry Perot interferometry, In First International Conference on Optical Fiber Sensors, London, 1993... 

Bidigare, R.R., and C.C. Trees. 2000. HPLC phytoplankton pigments Sampling, laboratory methods, and quality assurance procedures. Pp. 154-161 in Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 2, J. Mueller and G. Fargion, eds., NASA Technical Memorandum 2000-209966. 

Table 1.1 Summary of Recent and Current Satellite Ocean Color Sensors. ...

Kolusheva S, Shahal T, Jelinek R. Cation-selective color sensors composed of ionophore-phospholipid-polydiacetylene mixed vesicles. J Am Chem Soc 2000 122 776-780. 

In this review, Ii+, NH4+, and protein color sensors were treated with DCA analysis for the visual determination using several major advantages for its utilization in the calibration/determination of an analyte using color data as follows (1) calibration/determination based on numerical color data, (2) calibration/determination based on color library data, (3) calibration/determination based on chromaticity diagrams, and (4) suitable visual calibration/determination based on color simulating calibration which can be used for the design of an optimum color-based optode. 

The simplest color sensing systems are responsible for monitoring only one color across a scene. These are typically used in quality control applications such as monitoring of paints, to ensure consistency between batches made at different times. More sophisticated color sensors look at the color distribution across a two-dimensional image. These systems are capable of complex analysis and can be used for checking multi-colored labels or for identifying multi-colored objects by their color patterns. 

Phytoplankton blooms can be monitored also from space. The oceanographic ocean color sensors installed on satellites measure the visible and near-infrared spectral range to identify optically active water constituents, such as chlorophyll, yellow substance, and suspended matter, and to perform a required atmospheric correction. The polar orbit and the swath of most oceanographic sensors permit a daily coverage of the Baltic Sea with a spatial resolution of 1 km, or better. The synoptic character and the repeating rate allow studies of the spatial and temporal development of the phytoplankton nearly in real time. 

Vogeley L, Sineshchekov OA, Trivedi VD, Sasaki J, Spudich JL, Luecke H (2004) Anabaena sensory rhodopsin a photochromic color sensor at 2.0 A. Science 306 1390-1393... 

Observer Differences - The sensitivity of each individual s eyes is slightly different, even for people considered to have normal color vision. There maybe some bias toward blue o red. Blue, green and red are the primary colors of light because the eye has three types of cones (color sensors) which are sensitive to these three primary colors. This allows us to perceive color. Not all of our cones are exactly alike, making us bias to one color or another. Also, a persons eye sight changes with age. Because of these factors, color will appear sightly different to different observers. 

Robert D. Curtright, James A. Rynearson, and John Markwell, "Fruit Anthocyanins Colorful Sensors of Molecular Milieu," ]. Chem. Educ,... 

The model for multiple tracing robots divides each robot s CM into two levels of controllers, namely upper controller model (UCM) and lower controller model (LCM). The upper controller model deals with proximity sensors and wireless communication devices, while the lower controller model deals with color sensors and motors. Figure 2 shows the overview of the whole model. In Figure 2, Communication Medium Model is also used, which supports modeling for communication among proximity sensors and wireless communication devices. 

In-line/on-line feedback control of color of food during processing can improve not only color quality but also color related quality such as texture and appearance. To do this, there are three major aspects development of an in-line/on-line color sensor understanding of color change kinetics and establish correlations between instrumental measured and sensory panel perceived colors of foods. In this research, we have chosen color machine vision technology for the measurement of colors of food due to its superior spatial resolution over conventional instruments such as colorimeter or spectrophotometer. Relationships between measured colors and corresponding principal chemical markers were established for the model food systems. We have also found excellent correlations between the color machine vision system (CMVS) measured and a sensory panel determined colors of food samples (Ling and Tepper, 1995). We believed that a CMVS can be used for food process control to ensure color quality as perceived by consumers. 

Our research results also have demonstrated the feasibility of using CMV as a fast, non-destructive, in-line/on-line color sensor for a closed-loop controlled food process to produce high color quality food products. CMV was used, indirectly, to relate sensory panel perceived color quality and major pigment contents in food systems during diermal processes. The correlations between CMVS measured colors and human perceived colors of selected food models were established chemical markers were identified for color changes in thermal processes the correlations between external colors and principal pigment contents were established for two model food systems carrots and reformed beef cube. 

Fig. 17-13 Poly(3-hexyl-thiophene) based color sensor a) Structure ...

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