Fast model based feature matching technique applied to airport lighting

The use of image processing techniques to assess the performance of airport landing lighting using images of it collected from an aircraft-mounted camera is documented. In order to assess the performance of the lighting, it is necessary to uniquely identify each luminaire within an image and then track the luminaires through the entire sequence and store the relevant information for each luminaire, that is, the total number of pixels that each luminaire covers and the total grey level of these pixels. This pixel grey level can then be used for performance assessment. The authors propose a robust model-based (MB) featurematching technique by which the performance is assessed. The development of this matching technique is the key to the automated performance assessment of airport lighting. The MB matching technique utilises projective geometry in addition to accurate template of the 3D model of a landing-lighting system. The template is projected onto the image data and an optimum match found, using nonlinear least-squares optimisation. The MB matching software is compared with standard feature extraction and tracking techniques known within the community, these being the Kanade–Lucus–Tomasi (KLT) and scaleinvariant feature transform (SIFT) techniques. The new MB matching technique compares favourably with the SIFT and KLT feature-tracking alternatives. As such, it provides a solid foundation to achieve the central aim of this research which is to automatically assess the performance of airport lighting.

Simulation of coupled heat and moisture transfer in air-conditioned buildings

The simultaneous heat and moisture transfer in the building envelope has an important influence on the indoor environment and the overall performance of buildings. In this paper, a model for predicting whole building heat and moisture transfer was presented. Both heat and moisture transfer in the building envelope and indoor air were simultaneously considered; their interactions were modeled. The coupled model takes into account most of the main hygrothermal effects in buildings. The coupled system model was implemented in MATLAB-Simulink, and validated by using a series of published testing tools. The new program was applied to investigate the moisture transfer effect on indoor air humidity and building energy consumption under different climates. The results show that the use of more detailed simulation routines can result in improvements to the building's design for energy optimisation through the choice of proper hygroscopic materials, which would not be indicated by simpler calculation techniques.