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The Spectral Imaging (formerly known as SISM) project advances Australian capabilities in key emerging sensing technologies beyond the visible spectrum with a strong focus in national prosperity and well being. The project is one of the first of its kind worldwide combining a broad range of technologies to “see” beyond the visible spectrum and addressing the spectral image understanding problem making use of structural and statistical pattern recognition and computer vision techniques. |
The project has two main areas
Hyperspectral sensing
Hyperspectral imaging is an information-rich representation of the object under study in which each pixel or sample is comprised by a number of wavelength-indexed measurements. As a result, hyperspectral sensing is particularly well suited for non-intrusive material identification and recognition tasks with application in the areas of security, environment and biology.
Thermal and near-IR
Thermal and near-infrared imaging is a key technology in night-vision and surveillance applications. Thermography can also be used to monitor blood flow, body temperature and perform early, non-intrusive diagnosis of some kinds of cancer.
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Since spectral imaging is non-intrusive and non-destructive, we are working to provide more efficient, accurate, non-invasive and economical ways of monitoring the environment for preservation and security. To this end, we are developing diagnostic instruments and methods aimed at
To profit of these opportunities, NICTA and the CRC for National Plant Biosecurity (CRCNPB) have embarked in a A$1 million collaborative effort to enhance Australia's surveillance system aimed at exploiting the potential of hyperspectral imaging to pinpoint outbreaks or stressed plants within crops for the benefit of Australian competitiveness. |
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This technology can, potentially, save farmers and quarantine officers hundreds of hours in laborious and time-consuming pest inspections. As a result, the project produces research relevant to Australia’s DPI future in a multidisciplinary environment with collaborators from a number of state-government departments and research institutions nationwide. We are focusing on
These efforts have yielded promising preliminary results on the identification of a number of pests, such as some varieties of fruit fly and moth. Other promising results are those pertaining plant pathogens such as apple scab and wheat rust, amongst others. |
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The project was awarded the Best Paper Prize at the 6th IEEE Workshop on Object Tracking and Classification Beyond and in the Visible Spectrum (OTCBVS'09) for its work on hyperspectral image descriptors reported in the paper
Z. Fu and A. Robles-Kelly and T. Caelli and R. Tan, “On Automatic Absorption Detection for Imaging Spectroscopy: A Comparative Study”, In IEEE Transactions on Geoscience and Remote Sensing, Vol. 45(11-2), 3827-3844, 2007. ![]()
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