An Electronics Engineer with 15 years industrial experience as a Sensors and Instrumentations designer, particularly within the automated manufacturing and advanced display systems sectors.  The last 2 decades have been spent teaching and researching Analogue Electronics and Vision Sensors, both at Middlesex University and - in the last 7 years - at the University of East London.

• European Relations  and Recruitment
• Collaborative Links with EU institutions
• Collaborative Links (Engineering) with Turkish universities
• Chair of Recuitment & Promotion Group

• Electrical & Electronics Engineering (particularly Sustainable Technologies and Alternative Energy Systems)
• Sensors and Instrumentation Systems (particularly 3D Vision and Robotics sensors)
• E-Learning and On-line knowledge delivery technologies/methodologies

BEng (Hons) Electrical & Electronics Engineering

• Module Leader CE0103
• Module Leader CE0107
• Module Leader EE2401
• Module Leader EE3401

Second order mathematical model of an active 3D vision sensor (pending peer review - submitted to IEE Proceedings of Vision, Image and Signal Processing)

• Systematic Errors in Active 3D vision Sensors, IEE Proceedings of Vision, Image and Signal Processing; Vol 150, Mo6, Dec 2003, pp341-45
• plus 18 other published journal/conference papers in the field of Sensors and Robotics

• Robot Sensors and Transducers, Open University Press, 1987, ISBN 0-335-15408-5
• CEng
• MIEE
• MRSA
• MSPIE

Sensors are becoming increasingly widespread in applications ranging from mundane CCTV to complex automated industrial inspection and biometric security systems. Vision sensors used in industrial automation applications – particularly vision guided robot manipulation - can benefit from the use of mathematical models  - such as the Model Driven Image Acquisition (MDIA) algorithm - to help reduce the overall processing time.  However, mathematical models such as the MDIA can be adversely affected in applications where the objects to be imaged have surfaces with near-specular reflection characteristics (e.g. polished surfaces).

Work has been undertaken on the development, implementation and testing of an enhanced image acquisition algorithm for an active 3D vision sensor which overcomes such limitations by including secondary surface reflections within its mathematical model.  The results show a significant improvement when comparing the Matlab implementation of such an enhanced MDIA algorithm with the images obtained experimentally on 4 test pieces displaying both specular and non-specular surface characteristics.