No description available.

No description available.

No description available.

Attributes of colour images have been found which allow colour and lightness constancy to be computed without prior knowledge of the illumination, even in complex scenes with three -dimensional objects and multiple light sources of different colours. The ratio of surface reflectance colour can be immediately determined between any two image points, however distant. It is possible to determine the number of spectrally independent light sources, and to isolate the effect of each. Reflectance edges across which the illumination remains constant can be correctly identified. In a scene illuminated by multiple distant point sources of distinguishalbe colours, the spatial angle between the sources and their brightness ratios can be computed from the image alone. If there are three or more sources then reflectance constancy is immediately possible without use of additional knowledge. The results are an extension of Edwin Land's Retinex algorithm. They account for previously unexplained data such as Gilchrist's veiling luminances and his single- colour rooms. The validity of the algorithms has been demonstrated by implementing them in a series of computer programs. The computational methods do not follow the edge or region finding paradigms of previous vision mechanisms. Although the new reflectance constancy cues occur in all normal scenes, it is likely that human vision makes use of only some of them. In a colour image all the pixels of a single surface colour lie in a single structure in flux space. The dimension of the structure equals the number of illumination colours. The reflectance ratio between two regions is determined by the transformation between their structures. Parallel tracing of edge pairs in their respective structures identifies an edge of constant illumination, and gives the lightness ratio of each such edge. Enhanced noise reduction techniques for colour pictures follow from the natural constraints on the flux structures.

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The diverse visual specialisations of stomatopods are an important consideration in studies of their radiation and evolution. Most stomatopods in the Superfamilies Gonodactyloidea and Lysiosquilloidea have regionally specialised eyes. A central band composed of six rows of ommatidia contains an array of photoreceptive pigments and filters that allow for finely tuned colour and polarisation vision. In other stomatopods the mid-band is reduced and unspecialised, or is absent. Previously, this has been considered to be the plesiomorphic condition. Phylogenetic analyses of the Stomatopoda show that the extant stomatopod lineages evolved from a gonodactyloid-type ancestor. Characters for phylogenetic analyses have been derived from external morphology, details of eye daslqn and mitochondrial DNA sequences. Although not wholly congruent, the results from these separate analyses indicate that species with a simpler eye design are not more primitive but have lost parts of the mid-band arrangement. This regressive evolutionary event has occurred independently on a number of occasions. Observations on the neuroanatomy of the eyes in the stomatopod Neogonodactylus oerstedii have revealed the existence of an accessory lobe located distally on the medulla externa and connecting with the six mid-band rows. The lobe is involved in processing colour and polarisation information. The discovery of the lobe in species that lack the retinal specialisations for colour vision provides further evidence that they are descended from a more advanced ancestor. Similarities in the arrangement of eye muscles between species with a two or six row mid-band also give support for this conjecture. The ancestors of the modern stomatopods are likely to have evolved in shallow water and coral reef habitats. The development of colour vision was advantageous for prey location and in interspecific encounters. Stomatopods subsequently radiated into a diverse range of habitats. For those in more spectrally limited surroundings the colour vision system has largely been lost but vestiges are still present today in the form of a reduced mid-band and medulla lobe.

The perceived colour of an object depends on its spectral reflection and spectral composition of the illuminant. Upon illumination change, the light reflected from the object also varies. This results in a different colour sensation if no colour constancy mechanism is available to form consistent representations of colours across various illuminants. We explore various colour constancy mechanisms in an agent-based model of foraging bees selecting flower colour based on reward. The simulations are based on empirically determined spatial distributions of various flower species in different plant communities, their rewards and spectral reflectance properties. Simulated foraging bees memorise the colours of flowers experienced as being most rewarding, and their task is to discriminate against other flower colours with lower rewards, even in the face of changing illumination conditions. The experimental setup of the simulation of bees foraging under different photic environments reveals the performance of various colour constancy mechanisms as well as the selective pressures on flower colour as a result of changing light. We compared the performance of von Kries photoreceptor adaptation and various computational colour constancy models based on the retinex theory with (hypothetical) bees with perfect colour constancy, and with modelled bees with colour blindness. While each individual model generated moderate improvements over a colour-blind bee, the most powerful recovery of reflectance in the face of changing illumination was generated by computational mechanisms that increase perceptual distances between co-occurring colours in the scene. We verified the results of our model using various comparisons between modelled bees’ performance and that predicted by our models, as well as exploring the implications for flower colour distribution in a variety of representative habitats under realistic illumination conditions.

A colour may have a different appearance under different viewing conditions. This causes many problems in the colour reproduction industry. Thus the importance of prediction of colour appearance has arisen. In this study, a mathematical model to predict colour appearance was developed based on the investigation of the changes of colour appearance under a wide range of media and viewing conditions. The media studied included large cut-sheet transparency films, 35mm projected slides, reflection samples and monitor colours. The viewing conditions varied were light source, luminance level and viewing background. Colour appearance was studied using the magnitude estimation technique. In general, colours appeared more colourful, lighter and brighter with an increase in luminance level. Background and flare light had considerable influence on colour appearance for cut-sheet transparency media. Simultaneous contrast effects occurred when a monitor colour was displayed against a chromatic surround. The monitor colour appeared lighter with a darker induction field. When a coloured area was enlarged, lightness tended to increase while colourfulness tended to decrease. Colour appearance was also affected by the closest neighbouring colour. In this case, the hue of the colour largely shifted towards the direction of the opponent hue of the induction colour. The data obtained were applied to test three colour spaces and two colour appearance models. For reflection media, the Hunt91 model performed the best. However it was not satisfactory when applied to transmissive media. Based on these results, the Hunt93 model was developed by modification of the Hunt91 model. The new model widens the application range of the Hunt91 and is reversible.

In digital environments, colour is used for many purposes: for example, to encode information in charts, signify missing field information on websites, and identify active windows and menus. However, many people have inherited, acquired, or situationally-induced Colour Vision Deficiency (CVD), and therefore have difficulties differentiating many colours. Recolouring tools have been developed that modify interface colours to make them more differentiable for people with CVD, but these tools rely on models of colour differentiation that do not represent the majority of people with CVD. As a result, existing recolouring tools do not help most people with CVD. To solve this problem, I developed Situation-Specific Modelling (SSM), and applied it to colour differentiation to develop the Individualized model of Colour Differentiation (ICD). SSM utilizes an in-situ calibration procedure to measure a particular user’s abilities within a particular situation, and a modelling component to extend the calibration measurements into a full representation of the user’s abilities. ICD applies in-situ calibration to measuring a user’s unique colour differentiation abilities, and contains a modelling component that is capable of representing the colour differentiation abilities of almost any individual with CVD. This dissertation presents four versions of the ICD and one application of the ICD to recolouring. First, I describe the development and evaluation of a feasibility implementation of the ICD that tests the viability of the SSM approach. Second, I present revised calibration and modelling components of the ICD that reduce the calibration time from 32 minutes to two minutes. Next, I describe the third and fourth ICD versions that improve the applicability of the ICD to recolouring tools by reducing the colour differentiation prediction time and increasing the power of each prediction. Finally, I present a new recolouring tool (ICDRecolour) that uses the ICD model to steer the recolouring process. In a comparative evaluation, ICDRecolour achieved 90% colour matching accuracy for participants – 20% better than existing recolouring tools – for a wide range of CVDs. By modelling the colour differentiation abilities of a particular user in a particular environment, the ICD enables the extension of recolouring tools to helping most people with CVD, thereby reducing the difficulties that people with CVD experience when using colour in digital environments.

A project was sponsored by the SERC for research into the design of a colour vision system for the detection of print faults in rotary screen printed fabrics. The research was carried out at De Montfort University (formerly named Leicester Polytechnic), which has previous experience with Image Processing in relation to Textiles. The proposed system was required to identify, process and correct the common print faults which can occur during rotary screen printing. These can be divided into two main categories, systematic and random faults. This thesis covers the work undertakeni n the developmento f a laboratory-basedin spection systema ndt he subsequendte velopmenat nd testingo f methodologiesto facilitate factory-based on-line inspection. Initial investigation identified the requirement for colour segmentation algorithmsa ndt he researchin to anda nalysiso f suitablem ethodologiesf or segmentationf orms a fundamental part of this thesis. Important, new colour segmentation algorithms were developed from first principles by the author. These new methods offer improvements (in most cases significant) over the current `state-of-the-art' colour segmentation technology, and are applicable to a wide-range of computer vision tasks. These proposed methodologies have been rigorously tested and the findings of the investigation are presented as part of this thesis.