Supported by the Leverhulme Trust grant number F/00 094/M
The image is considered to be the product of the interaction of light with the constituents of the scene. The physics of light transport is utilised to construct a spectral characterisation model - a mathematical model capable of predicting the range of colouration expected from materials known to occur within the scene. By comparing image data to these predictions material characteristics can be deduced.
Our group has successfully applied this approach to develop a novel skin imaging system [4-5]. From two images of the skin, one colour and one acquired through a near-infrared filter, informative parametric maps are computed, containing detailed information about the concentration of melanin and blood and collagen thickness across the imaged skin . Current medical trials are showing the maps to be of great value in the diagnosis of melanoma .
The specific objectives of this work are to:
The key novelty of our approach is in its development and exploitation of the spectral characterisation models of specific materials. The structure of the model allows us to create a simple cross-reference between the object composition and its colour (or some richer spectral characterisation). As the model is constructed using physics (rather than, for example, statistics) the physical origin of colours seen in images can be explained with reference to the actual physical phenomena. The mathematical form of the model allows us to take advantage of the well developed spectrophotometric quantitative methodologies whilst presenting the results as images, which convey rich spatial information.
The practical significance of the proposed method is that for suitable classes of materials, quantitative estimates of their composition can be obtained from their image data. The method is instant and non-invasive. Once a set of optical filters is defined for a given class of material, the filtering during the image acquisition phase followed by nearly real time post-processing enables appropriate image sets to be presented for interpretation. The underlying scientific technique is fundamentally generic and is the potential basis of a unique non-destructive testing technology which does not require complex equipment and could be implemented using only a digital camera with filters. The applicability of the method to a given class of materials can be assessed due to the underlying predictive theory.
A spectrum specifies the light levels associated with each of several hundred discrete spectral wavelengths. Although it is possible to acquire digital images corresponding to many wavelengths, this is costly in terms of storage space and processing time. Standard colour video cameras "compress" the whole light spectrum to just three components: red, green and blue. This is achieved by filtering the incoming light through red, green and blue filters. Most people find that this represents images quite adequately, because these three filters are tuned to the colours that the human visual system perceives best. These filters are, however, unlikely to be the best choice for all the materials. One of the most important parts of the project is to develop general methods for defining filters which would be most appropriate for specific materials. An ideal filter will produce an image showing even small variations in a property of a single component of a material. There exist statistical and mathematical methods for finding such "optimal" filters.
Finally, to evaluate the methodology, the developed techniques will be practically applied to images from two different domains. Possible candidate domains include agriculture, ophthalmology and remote sensing.
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