Name
Abstract | ||
|---|---|---|
Medical tests such as urinalysis, and other colori-metric assays require the measurement of changes in color. For such applications, this paper presents an innovative, low-cost color sensor, based on reflective color sensing. The proffered system is constituted of a light-intensity sensor and an RGB (red, green, blue) LED, placed on strategic geometries. Various regression models for calibration of the color sensor were investigated. Using cross validation with a training set of 160 colors, a cubic-spline regression model was selected. The accuracy and robustness of the novel sensor are also discussed. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ISED.2018.8704102 | 2018 8th International Symposium on Embedded Computing and System Design (ISED) |
Keywords | Field | DocType |
Color,Robot sensing systems,Computational modeling,Solid modeling,Calibration,Light emitting diodes | Training set,Computer vision,Regression analysis,Computer science,Robustness (computer science),Solid modeling,RGB color model,Artificial intelligence,Light-emitting diode,Cross-validation,Calibration | Conference |
ISBN | Citations | PageRank |
978-1-5386-6575-6 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Harikrishnan Venugopal | 1 | 0 | 0.68 |
| Akshay Jayakumar | 2 | 4 | 0.75 |
| Georg Gutjahr | 3 | 0 | 2.37 |
| G J Nair | 4 | 0 | 0.34 |
| Prema Nedungadi | 5 | 33 | 13.10 |