Abstract: An image processing method includes partitioning an image under test to form a plurality of contiguous image segments having similar image properties, deriving feature data from a subset including one or more of the image segments, and comparing the feature data from the subset of image segments with feature data derived from respective image segments of one or more other images so as to detect a similarity between the image under test and the one or more other images.

Abstract: An image processing method includes partitioning an image under test to form a plurality of contiguous image segments having similar image properties, deriving feature data from a subset including one or more of the image segments, and comparing the feature data from the subset of image segments with feature data derived from respective image segments of one or more other images so as to detect a similarity between the image under test and the one or more other images.

Abstract: An image processing method includes partitioning an image under test to form a plurality of contiguous image segments having similar image properties, deriving feature data from a subset including one or more of the image segments, and comparing the feature data from the subset of image segments with feature data derived from respective image segments of one or more other images so as to detect a similarity between the image under test and the one or more other images.

Abstract: An image processing method includes partitioning an image under test to form a plurality of contiguous image segments having similar image properties, deriving feature data from a subset including one or more of the image segments, and comparing the feature data from the subset of image segments with feature data derived from respective image segments of one or more other images so as to detect a similarity between the image under test and the one or more other images.

Abstract: An image processing method includes partitioning an image under test to form a plurality of contiguous image segments having similar image properties, deriving feature data from a subset including one or more of the image segments, and comparing the feature data from the subset of image segments with feature data derived from respective image segments of one or more other images so as to detect a similarity between the image under test and the one or more other images.

Abstract: An image processing method includes partitioning an image under test to form a plurality of contiguous image segments having similar image properties, deriving feature data from a subset including one or more of the image segments, and comparing the feature data from the subset of image segments with feature data derived from respective image segments of one or more other images so as to detect a similarity between the image under test and the one or more other images.

Abstract: A method of organising data items in an n-dimensional space comprises, for each of a plurality of iterations, the step of generating a relative displacement of position for each data item within the n-dimensional space in accordance with a similarity value between each data item and respective other data items, the distance between each data item and respective other data items in the n-dimensional space, and the difference in position within the n-dimensional space between each data item and at least one reference point.

Abstract: An image processing method includes detecting statistical distribution of permutations of pixel properties amongst contiguous groups of a predetermined number of pixels in at least a portion of an image under test, so as to derive feature data in respect of the image under test, and comparing the feature data derived in respect of the image under test with feature data derived from at least respective portions of one or more other images so as to detect a similarity between the image under test and the one or more other images.

Abstract: An information handling method in which information items are mapped to respective nodes in an array of nodes by mutual similarity of the information items, such that similar information items map to nodes at similar positions in the array of nodes; a mapping relationship being defined between feature data relating to an information item and nodes in the array of nodes comprises the steps of: (a) for each of a group of information items: detecting feature data representing each of a set of properties of that information item; (b) for the ensemble of feature data corresponding to the group of information items: detecting more significant and less significant properties within the ensemble; discarding feature data relating to less significant properties, the remaining non-discarded feature data being associated so as to generate a reduced feature vector for each information item; (c) defining a mapping between the reduced feature vectors and nodes in the array of nodes.

Abstract: A method of organising data items in an n-dimensional space comprises, for each of a plurality of iterations, the step of generating a relative displacement of position for each data item within the n-dimensional space in accordance with a similarity value between each data item and respective other data items, the distance between each data item and respective other data items in the n-dimensional space, and the difference in position within the n-dimensional space between each data item and at least one reference point.

Abstract: A method of organizing data items in an n-dimensional space comprises, for each of a plurality of iterations, the step of generating a relative displacement of position for each data item within the n-dimensional space in accordance with a similarity value between each data item and respective other data items, the distance between each data item and respective other data items in the n-dimensional space, and the difference in position within the n-dimensional space between each data item and at least one reference point.

Abstract: An image processing method includes detecting statistical distribution of permutations of pixel properties amongst contiguous groups of a predetermined number of pixels in at least a portion of an image under test, so as to derive feature data in respect of the image under test, and comparing the feature data derived in respect of the image under test with feature data derived from at least respective portions of one or more other images so as to detect a similarity between the image under test and the one or more other images.

Abstract: An image processing method includes partitioning an image under test to form a plurality of contiguous image segments having similar image properties, deriving feature data from a subset including one or more of the image segments, and comparing the feature data from the subset of image segments with feature data derived from respective image segments of one or more other images so as to detect a similarity between the image under test and the one or more other images.

Abstract: A method of organising data items in an n-dimensional space comprises, for each of a plurality of iterations, the step of generating a relative displacement of position for each data item within the n-dimensional space in accordance with a similarity value between each data item and respective other data items, the distance between each data item and respective other data items in the n-dimensional space, and the difference in position within the n-dimensional space between each data item and at least one reference point.