7 research outputs found
Characterization and Performance of a Thermal Camera Communication System
This work presents a novel communications technology named Thermal Camera Communication (TCC), which is analogous to Optical Camera Communication (OCC). Thermographic cameras and Peltier cells are proposed as receiver and transmitter, respectively, changing completely their usual field of application. Furthermore, a comprehensive characterization of the Peltier–Thermal camera pair is carried out, presenting their bandwidth, achievable data rate under On-Off-Keying (OOK) modulation, noise characteristics, and energy efficiency. A comparison against the current state-of-the-art OCC technology is also provided, showing that TCC is a promising technology suitable for sensor networks. The thorough analysis of TCC performed in this work shows that commercial Peltier cells can be re-thought under a communications viewpoint in order to improve their performance. This novel communication technology can be applied in environments such as the access to public transportation or buildings due to the new health emergency situation. The use of thermographic cameras will become massive and dual measurement and communication purposes could be considered for applications such as sensor networks, using a yet unexploited wavelength range
15+ MILLION TOP 1% MOST CITED SCIENTIST 12.2% AUTHORS AND EDITORS FROM TOP 500 UNIVERSITIES Chapter from the book Advanced Biometric Technologies Downloaded from: http://www.intechopen.com/books/advanced-biometric- technologies 11 A Gender Detection Appro
Pollen classification based on geometrical, descriptors and colour features using decorrelation stretching method
Abstract. Saving earth's biodiversity for future generations is an important global task, where automatic recognition of pollen species by means of computer vision represents a highly prioritized issue. This work focuses on analysis and classification stages. A combination of geometrical measures, Fourier descriptors of morphological details using Discrete Cosine Transform (DCT) in order to select their most significant values, and colour information over decorrelated stretched images are proposed as pollen grains discriminative features. A MultiLayer neural network was used as classifier applying scores fusion techniques. 17 tropical honey plant species have been classified achieving a mean of 96.49% 1.16 of success