Research Report - 2001
CSSIP
Qld Node Director
Prof Dennis Longstaff
Academic Staff
Prof Dennis Longstaff
A/Prof Brian Lovell
Dr John Homer
Senior Research Staff
Dr Glen Callaghan (ARC)
Dr Paul Jackway
Dr Chris Leat (ARC)
Dr David Lloyd (ARC)
Dr David Noon
Dr Rupert Paget (ARC)
Dr Glen Stickley
Prof Vassilios Sarafis
Dr Pascal Bamford
Mr Bryan Reeves
Research Students
Mr Robert Andrews
Mr Pat Bellett
Mr Aaron Chong
Mr Richard Davis
Mr Damian Jones
Mr Kim Hsin-Jung Lai
Mr Nianjun Liu
Mr Andrew Mehnert
Mr Bryan Reeves
Mr Martin Robinson
Contact Details
Prof Dennis Longstaff
Email: idl@csee.uq.edu.au
Tel: 3365 3871
A/Prof Brian Lovell
Email: lovell@csee.uq.edu.au
Tel: 3365 4134
Dr John Homer
Email: homerj@csee.uq.edu.au
Tel: 3365 4139
Webpages
www.cssip.uq.edu.au/home
CSSIP Annual Report 1999/00
Available from Mr G Vaughan-Evans
Tel: 61-8-8302 3923
A wide variety of sensors are used in applications ranging from mining to defence and from medicine to navigation. The important information collected by such sensors often has very high data rates and may be overwhelmed by extraneous signals. With the advent of very precise analog-to-digital converters, high power computing technology and powerful digial signal processing hardware, a significant improvement in sensor performance is possible.
Staff and students working in this field form a node of the Cooperative Research Centre for Sensor Signal and Information Processing (CSSIP). This is a collaborative venture between The University of Adelaide, Flinders University, The University of South Australia, The University of Melbourne, The University of Queensland, DSTO, Compaq, Telstra, RLM, and CEA Technologies Pty Ltd.
The CSSIP Queensland node is active in the main research areas of radar signal processing, mining sensors and cytometrics. We encourage high calibre and enthusiastic postgraduate students to join our research centre. Some of our staff are not funded by the CRC program, but are supported by ARC and SPIRT grants, but enjoy the benefit of being co-located with the CRC.
Mining Sensors
The high-technology sensors such as radar, sonar, laser and optics are becoming increasingly important for the mining industry. The Mining Sensors group has been developing the stepped-frequency ground penetrating radar (GPR) technique for over seven years. Our second generation technology has now demonstrated significant improvements over the "first generation" impulse GPR systems, with prospects of new applications in mining and for commercialising the radar system.
Another current project is to use a ground-based radar sensor with interferometric processing to monitor the stability of pit walls during highwall mining. This has demonstrated an ability to measure movements to less than a millimeter and produce a map of time varying motion. More information on this project can be obtained from http://www.cssip.uq.edu.au/highwall/highmain.html
The Ground Penetrating Radar and the Slope Stability Radar will be available commercially through a new company GroundProbe Pty Ltd. The group closely collaborates with the CRC for Mining Technology and Equipment (CMTE), and scholarships are available for new postgraduate students in the Mining Sensors group.
Cytometrics
Cytometrics is the application of computer vision, image analysis, and pattern recognition techniques to the detection of cancer and neoplasia (early pre-cancer) on pathology slides. The CSSIP Cytometrics project is developing software for the automated screening of Pap smear slides for the detection of cervical cancer. A collaboration agreement has been reached with AccuMed, a Chicago based supplier of automated cytometers, to develop image processing and classification tech- niques. This should lead to improved efficiency, accuracy and sensitivity of cancer detection in pathology laboratories.
Computers can detect and measure changes too small to be visible to the human eye and can therefore give new information on the degree of abnormality. Such systems may be useful in a wide range of diseases and diagnostic tests using slides. The project currently focuses on the detection of early changes in the visual appearance of cell nuclei caused by pre-cancerous changes at a lesion nearby in the body. Research on the detection of abnormalities within the cell nucleus using improvements on conventional image texture techniques has produced very encouraging results. Several completed PhD projects have produced a suite of very powerful abnormality detection algorithms using "image texture" in the cell nucleus as a diagnostic marker.
Synthetic Aperture Radar Imaging
Synthetic Aperture Radar (SAR) systems provide high resolution 2- dimensional images of the ground, irrespective of atmospheric or illumination conditions. SAR im- ages, which may be acquired from spaceborne or ground-based sys- tems, contain both reflectivity and phase information. Research is aimed at: generation of high quality 3-dimensional images of terrain through `multi-baseline interferometric' processing of a series of spaceborne SAR images acquired over the same terrain; development of radar waveform diversity and array null steering techniques to increase the swath width of spaceborne SAR systems; development of SAR image texture modelling techniques to enable segmentation/classification of the different terrain types; development of clutter modelling and suppression techniques for ground-based ultra-wide band SAR so as to improve the detectibility of, for example, land-mines. The research has attracted consultancy work with NASA's Jet Propulsion Laboratory and the Australian Antarctic Division as well as collaborationwith the Australian Centre for Remote Sensing and the Defence Science and Technology Organisation (DSTO).
Computational Electromagnetics
Computational Electromagnetics is involved with computer modeling of electromagnetic phenomena. The huge increase in computational resources available permits the rigorous analysis of increasingly sophisticated problems.
Current research carried out within this sub-group includes:
The design of antennas for Ground Probe Radar (GPR) and the characterisation of unexploded ordnance and plastic landmines for detection with ultra-wideband GPR.
Models for Ground Penetrating Radar (GPR) Antennas and in-Ground Targets
Our work focuses on the electro- magnetic methods of detection. We must know the behaviour of both the GPR antennas and the mines and UXOs, in order to improve GPR performance and to evaluate novel means to improve the detection of mines and UXOs in a controlled environment. GPR antennas are normally placed in close proximity to the ground. The antenna and its environment interact in a complicated fashion that has required a heavy reliance upon experimental and physical scale modeling. Numerical models on the other hand, mesh the entire antenna and numerically solve an integral equation for the unknown current on the structure. From this result, the electromagnetic field behaviour in both the near and far field of the radiator may be accurately determined. Likewise, small GPR targets may be embedded in or below the surface. Targets such as plastic landmines are difficult to detect with a GPR so we are interested in special characteristics, such as resonant frequencies, which may aid detection. The results of this program now allow accurate and complete computer design of the radiators used in GPR as well as provide insight into many of the phenomena observed in empirical and experimental testing of the radar with different conducting targets. We are currently generalizing the model to the case of a dielectric scatterer situated below the surface in the near field illumination of an antenna. The methods used are rigorous and are valid for ultra wide band applications. The antenna design work has led to the development of a novel three- dimensional GPR antenna. Researchers in this field can combine solving important practical problems with contributing to the understanding of the fundamental physical phenomenon of electro- magnetism in a broad sense.
Significant Publications
Jackway,P.,"On the Scale Space-Theorem of Chen and Yan", IEEE Trans PAMI, 20(3), pp203-213 1998.
Paget, R. and Longstaff, I.D., "Texture synthesis via a noncausal nonparametric multiscale Markov random field", IEEE Transactions on Image Processing, 7(6), 925- 931, June 1998.
Callaghan, G.D., and Longstaff, I.D., "Wide Swath Spaceborne SAR Using a Quad Element Aray", IEE Proceedings - Radar Sonar and Navigation. Vol 146, No 3, pp 159-165, June 1999.
Cherniakov, M. and Donskoi, L., "Frequency Band Selection of radars for Buried Object Detection", IEEE Trans IGRS, Vol 37, No2, Pp 838-845, March 1999.
Gunawardina, A. and Longstaff, I.D.,"Wave Equation Formulation for Synthetic Aperture Radar Algorithms in the Time-Space Domain", IEEE Trans IGRS Vol 36, No6, pp 1995-1999, 1998.
Leat C.J., Shuley N.V., and Stickley, G.F., "Complex image model for Ground Penetrating Radar Antennas" IEEE Transactions, Antennas and Propagation, vol. 46, no. 10, October , 1998, pp 1438-1488.
Wang Y, Longstaff I D, Leat C J, and Shuley, N.V. “Complex natural resonance of conducting planar objects buried in a dielectric halfspace” . IEEE Trans Geoscience and Remote Sensing IGRSD2 Vol 39, No 6, June 2001.
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