James Niblock

Automated Object Identification and Position Estimation for Airport Lighting Quality Assessment

The development of an automated system for the quality assessment of aerodrome ground lighting (AGL), in accordance with associated standards and recommendations, is presented. The system is composed of an image sensor, placed inside the cockpit of an aircraft to record images of the AGL during a normal descent to an aerodrome. A model-based methodology is used to ascertain the optimum match between a template of the AGL and the actual image data in order to calculate the position and orientation of the camera at the instant the image was acquired. The camera position and orientation data are used along with the pixel grey level for each imaged luminaire, to estimate a value for the luminous intensity of a given luminaire. This can then be compared with the expected brightness for that luminaire to ensure it is operating to the required standards. As such, a metric for the quality of the AGL pattern is determined. Experiments on real image data is presented to demonstrate the application and effectiveness of the system.

An Automated System for Performance Assessment of Airport Lighting

This paper presents work undertaken into the development of an automated air-based vision system for assessing the performance of an approach lighting system (ALS) installation in accordance with International Civil Aviation Organisation (ICAO) standards. The measuring device consists of an image sensor with associated lens system fitted to the interior of an aircraft. The vision system is capable of capturing sequences of airport lighting images during a normal approach to the airport. These images are then processed to determine the uniformity of the ALS. To assess the uniformity of the ALS the luminaires must first be uniquely identified and tracked through an image sequence. A model-based matching technique is utilised which uses a camera projection system to match a set of template data to the extracted image data. From the matching results the associated position and pose of the camera is estimated. Each luminaire emits an intensity which is dependant on its angular displacement from the camera. As such, it is possible to predict the intensity that each luminaire within the ALS emits during an approach. Luminaires emitting the same intensity are banded together for the uniformity analysis. Uniformity assumes that luminaires in close proximity exhibit similar luminous intensity characteristics. During a typical approach grouping information is obtained for the various sectors of luminaires. This grouping information is used to compare luminaires against one another in terms of their extracted grey level information. The developed software is validated using data acquired during an actual approach to a UK airport.

An Iterative Algorithm for Finding Point Correspondences

This paper presents a solution to a general correspondence problem between a set of points (or image features) and a template, where the matching criterion includes linear parameters which reflect dynamic camera zooming during image-based tracking procedures. An algorithm is proposed which will solve this type of correspondence problem. Unlike most existing algorithms, which approach the solution using relaxation and mathematical programming, the proposed algorithm searches for the solution by iteratively interchanging the position of feature-pairs within the feature set until a necessary condition is satisfied. This being, if the interchange of two features from the feature set degrades the matching criterion. Three sets of correspondence examples are detailed which illustrate the effectiveness and efficiency of the proposed correspondence technique in solving cases, or image data, which are affected by large translation and scaling. A standard technique, the Scott and Longuet-Higgins method, taken from literature is also tested as a comparison.

An Imaging System that Autonomously Monitors Lighting Patterns with Application to Airport Lighting

This paper presents a novel measurement system that assesses the uniformity of a complete airport lighting installation. The system improves safety with regard to aircraft landing procedures by ensuring airport lighting is properly maintained and conforms to current standards and recommendations laid down by the International Civil Aviation Organisation. The measuring device consists of a CMOS vision sensor with associated lens system fitted to the interior of an aircraft. The vision system is capable of capturing sequences of airport lighting images during a normal approach to an aerodrome. These images are then post processed to determine the uniformity of the complete pattern. Airport lighting consists of elevated approach and inset runway luminaires. Each luminaire emits an intensity which is dependant on the angular displacement from the luminaire. For example, during a normal approach a given luminaire will emit its maximum intensity down to its minimum intensity as the aircraft approaches and finally passes over the luminaire. As such, it is possible to predict the intensity that each luminaire within the airport lighting pattern emits, at a given time, during a normal approach. Any luminaires emitting the same intensity can then be banded together for the uniformity analysis. Having derived the theoretical groups of similar luminaires within a standard approach, this information was applied to a sequence of airport lighting images that were recorded during an approach to Belfast International Airport. Since we are looking to determine the uniformity of the pattern, only the total pixel grey level representing each luminaire within each banded group needs to be extracted and tracked through the entire image sequence. Any luminaires which fail to meet the requirements (i.e. a threshold value depending on the performance of the other luminaires in that band) are monitored and reported to the assessor for attention. The extraction and tracking algorithms have been optimised for minimal human intervention. Techniques such as component analysis as well as centre of mass algorithms are used to detect and locate the luminaires. A search algorithm is used to obtain the brightness (total grey level) of each luminaire. For the sample test at Belfast International Airport several luminaires were found that do not output sufficient intensity. As a final conclusion however, the Belfast International lighting pattern is legal and conforms to standards as no two consecutive luminaires fail in the pattern. The techniques used in this paper are novel. No known research exists that couples uniformity of airport lighting with photometrics. A solid basis has been established for future work on monitoring the individual characteristics of the luminaires. This includes colour and intensity measurements.