Geographic Information Science & Technology Body of Knowledge
Influenced by the four-category ontology of Aristotle, many modern ontologies treat shapes as acc... more Influenced by the four-category ontology of Aristotle, many modern ontologies treat shapes as accidental particulars which (a) are specifically dependent on the substantial particulars which act as their bearers, and (b) instantiate accidental universals which are exemplified by those bearers. It is also common to distinguish between, on the one hand, these physical shapes which form part of the empirical world and, on the other, ideal geometrical shapes which belong to the abstract realm of mathematics. Shapes of the former kind are often said to approximate, but never to exactly instantiate, shapes of the latter kind. Following a suggestion of Frege, ideal mathematical shapes can be given precise definitions as equivalence classes under the relation of geometrical similarity. One might, analogously, attempt to define physical shape universals as equivalence classes under a relation of physical similarity, but this fails because physical similarity is not an equivalence relation. In this talk I will examine the implications of this for the ontology of shape and in particular for the relationship between mathematical shapes and the shapes we attribute to physical objects.
We propose a taxonomy of part-types based on the manner of attachment of a part to the rest of it... more We propose a taxonomy of part-types based on the manner of attachment of a part to the rest of its parent whole, its degree of dependence on that whole or on external factors, and the temporal relation between its being a part and its being described as such.
Where a licence is displayed above, please note the terms and conditions of the licence govern yo... more Where a licence is displayed above, please note the terms and conditions of the licence govern your use of this document. When citing, please reference the published version. Take down policy While the University of Birmingham exercises care and attention in making items available there are rare occasions when an item has been uploaded in error or has been deemed to be commercially or otherwise sensitive.
SummaryWe present an approach for automatic threshold segmentation of greyscale images. The proce... more SummaryWe present an approach for automatic threshold segmentation of greyscale images. The procedure is inspired by a reinterpretation of the strategy observed in human operators when adjusting thresholds manually and interactively by means of ‘slider’ controls. The approach translates into two methods. The first one is suitable for single or multiple global thresholds to be applied globally to images and consists of searching for a threshold value that generates a phase whose boundary coincides with the largest gradients in the original image. The second method is a variation, implemented to operate on the discrete connected components of the thresholded phase (i.e. the binary regions) independently. Consequently, this becomes an adaptive local threshold procedure, which operates relative to regions, rather than to local image subsets as is the case in most local thresholding methods previously published. Adding constraints for specifying certain classes of expected objects in the...
We present an approach for automatic threshold segmentation of greyscale images. The procedure is... more We present an approach for automatic threshold segmentation of greyscale images. The procedure is inspired by a reinterpretation of the strategy observed in human operators when adjusting thresholds manually and interactively by means of 'slider' controls. The approach translates into two methods. The first one is suitable for single or multiple global thresholds to be applied globally to images and consists of searching for a threshold value that generates a phase whose boundary coincides with the largest gradients in the original image. The second method is a variation, implemented to operate on the discrete connected components of the thresholded phase (i.e. the binary regions) independently. Consequently, this becomes an adaptive local threshold procedure, which operates relative to regions, rather than to local image subsets as is the case in most local thresholding methods previously published. Adding constraints for specifying certain classes of expected objects in the images can improve the output of the method over the traditional 'segmenting first, then classify' approach. Materials and methods The conventions used in this paper are as follows. 'Phase' is the set of all pixels labelled as foreground at some tentative threshold value. 'Regions' are sets of pixels belonging to the phase that are locally connected under 8-neighbours connectivity, whereas 'objects' are those regions that correspond to
We propose a taxonomy of part-types based on the manner of attachment of a part to the rest of it... more We propose a taxonomy of part-types based on the manner of attachment of a part to the rest of its parent whole, its degree of dependence on that whole or on external factors, and the temporal relation between its being a part and its being described as such.
At a finer granularity it looks more discrete: the successive addition of new buildings, streets,... more At a finer granularity it looks more discrete: the successive addition of new buildings, streets, etc. At a finer granularity still all these events consist of the continuous motion of matter.
Signal Processing-image Communication, Aug 1, 2019
This paper shows how the Discrete Mereotopology notions of adjacency and neighbourhood between re... more This paper shows how the Discrete Mereotopology notions of adjacency and neighbourhood between regions can be exploited through Mathematical Morphology to accept or reject changes resulting from traditional morphological operations such as closing and opening. This leads to a set of six morphological operations (here referred to generically as minimal opening and minimal closing) where minimal changes fulfil specific spatial constraints. We also present an algorithm to compute the RCC5D and RCC8D relation sets across multiple regions resulting in a performance improvement of over three orders of magnitude over our previously published algorithm for Discrete Mereotopology.
Influenced by the four-category ontology of Aristotle, many modern ontologies treat shapes as acc... more Influenced by the four-category ontology of Aristotle, many modern ontologies treat shapes as accidental particulars which (a) are specifically dependent on the substantial particulars which act as their bearers, and (b) instantiate accidental universals which are exemplified by those bearers. It is also common to distinguish between, on the one hand, these physical shapes which form part of the empirical world and, on the other, ideal geometrical shapes which belong to the abstract realm of mathematics. Shapes of the former kind are often said to approximate, but never to exactly instantiate, shapes of the latter kind. Following a suggestion of Frege, ideal mathematical shapes can be given precise definitions as equivalence classes under the relation of geometrical similarity. One might, analogously, attempt to define physical shape universals as equivalence classes under a relation of physical similarity, but this fails because physical similarity is not an equivalence relation. In this talk I will examine the implications of this for the ontology of shape and in particular for the relationship between mathematical shapes and the shapes we attribute to physical objects.
Proceedings of the 2010 conference on Formal Ontology in Information Systems: Proceedings of the Sixth International Conference (FOIS 2010)
Formal Ontology in Information Systems, Jul 29, 2010
Epithelium and stroma segmentation using multiscale superpixel clustering
Introduction: Accurate image segmentation is essential in quantitative histopathology although ch... more Introduction: Accurate image segmentation is essential in quantitative histopathology although challenging due to tissue complexity, heterogeneity and the uncertainty of scene contents. Because structures detected at certain resolutions do not always coincide with the resolution at which other features are detected, we investigated a multiscale approach of image segmentation. Method: We developed an unsupervised framework using multiscale superpixels and k-means clustering. Images were partitioned into increasingly sized superpixels and clustered into 3 classes based on tissue stain uptake after colour deconvolution (aiming to identify background, epithelium and stroma) in H&E oropharyngeal cancer TMA sections. To overcome arbitrary label assignments during clustering, labelled regions were sequentially matched across consecutive scale image pairs using the additive inverse of the Dice index to generate a ‘cost matrix’ for all label combinations. A bipartite graph matching algorithm identified the combination that minimised the matrix overall cost. Results: From the matched ensemble, labelling probability images were generated to compute a ‘most likely’ segmentation. Fifty-six micro-array images compared with annotated standards achieved an average Dice index of 0.76 (median 0.79). The ‘most likely’ segmentations versus the standard, achieved a higher Dice index than those of the smallest and largest scale results (71% and 95% of instances respectively) and the average Dice over all scales (in 93% of instances). Conclusions: Our unsupervised segmentation, on average, performs better than single resolution superpixel clusterings. The method can also be applied to samples stained by other methods, once the dye RGB vectors (for colour deconvolution) have been appropriately determined.
Evolution of connections in SHRUTI networks
SHRUTI is a model of how predicate relations can be represented and reasoned upon using a network... more SHRUTI is a model of how predicate relations can be represented and reasoned upon using a network of spiking neurons, attempting to model the brain’s ability to perform reasoning using as biologically plausible a means as possible. This paper extends the biological plausibility of the SHRUTI model by presenting a genotype representation of connections in a SHRUTI network using indirect encoding and showing that working networks represented in this way can be produced through an evolutionary process. A multi-objective algorithm is used to minimise the error and the number of weight changes that take place as a network learns.
SHRUTI is a model of how predicate relations can be represented and reasoned upon using a network... more SHRUTI is a model of how predicate relations can be represented and reasoned upon using a network of spiking neurons, attempting to model the brain’s ability to perform reasoning using as biologically plausible a means as possible. This paper extends the biological plausibility of the SHRUTI model by presenting a genotype representation of connections in a SHRUTI network using indirect encoding and showing that working networks represented in this way can be produced through an evolutionary process. A multi-objective algorithm is used to minimise the error and the number of weight changes that take place as a network learns.
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Papers by Antony Galton