23,516 research outputs found

    Representation of Imprecise Digital Objects

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    International audienceIn this paper, we investigate a new framework to handle noisy digital objects. We consider digital closed simple 4-connected curves that are the result of an imperfect digital conversion (scan, picture, etc), and call digital imprecise contours such curves for which an imprecision value is known at each point. This imprecision value stands for the radius of a ball around each point, such that the result of a perfect digitization lies in the union of all the balls. In the first part, we show how to define an imprecise digital object from such an imprecise digital contour. To do so, we define three classes of pixels : inside, outside and uncertain pixels. In the second part of the paper, we build on this definition for a volumetric analysis (as opposed to contour analysis) of imprecise digital objects. From so-called toleranced balls, a filtration of objects, called λ-objects is defined. We show how to define a set of sites to encode this filtration of objects

    Voronoi-Based Region Approximation for Geographical Information Retrieval with Gazetteers

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    Gazetteers and geographical thesauri can be regarded as parsimonious spatial models that associate geographical location with place names and encode some semantic relations between the names. They are of particular value in processing information retrieval requests in which the user employs place names to specify geographical context. Typically the geometric locational data in a gazetteer are confined to a simple footprint in the form of a centroid or a minimum bounding rectangle, both of which can be used to link to a map but are of limited value in determining spatial relationships. Here we describe a Voronoi diagram method for generating approximate regional extents from sets of centroids that are respectively inside and external to a region. The resulting approximations provide measures of areal extent and can be used to assist in answering geographical queries by evaluating spatial relationships such as distance, direction and common boundary length. Preliminary experimental evaluations of the method have been performed in the context of a semantic modelling system that combines the centroid data with hierarchical and adjacency relations between the associated place names

    Representation of uncertain multichannel digital signal spaces and study of pattern recognition based on metrics and difference values on fuzzy n-cell number spaces

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    In this paper, we discuss the problem of characterization for uncertain multichannel digital signal spaces, propose using fuzzy n-cell number space to represent uncertain n-channel digital signal space, and put forward a method of constructing such fuzzy n-cell numbers. We introduce two new metrics and concepts of certain types of difference values on fuzzy n -cell number space and study their properties. Further, based on the metrics or difference values appropriately defined, we put forward an algorithmic version of pattern recognition in an imprecise or uncertain environment, and we also give practical examples to show the application and rationality of the proposed technique

    Geographical information retrieval with ontologies of place

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    Geographical context is required of many information retrieval tasks in which the target of the search may be documents, images or records which are referenced to geographical space only by means of place names. Often there may be an imprecise match between the query name and the names associated with candidate sources of information. There is a need therefore for geographical information retrieval facilities that can rank the relevance of candidate information with respect to geographical closeness of place as well as semantic closeness with respect to the information of interest. Here we present an ontology of place that combines limited coordinate data with semantic and qualitative spatial relationships between places. This parsimonious model of geographical place supports maintenance of knowledge of place names that relate to extensive regions of the Earth at multiple levels of granularity. The ontology has been implemented with a semantic modelling system linking non-spatial conceptual hierarchies with the place ontology. An hierarchical spatial distance measure is combined with Euclidean distance between place centroids to create a hybrid spatial distance measure. This is integrated with thematic distance, based on classification semantics, to create an integrated semantic closeness measure that can be used for a relevance ranking of retrieved objects

    Fuzzy heterogeneous neurons for imprecise classification problems

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    In the classical neuron model, inputs are continuous real-valued quantities. However, in many important domains from the real world, objects are described by a mixture of continuous and discrete variables, usually containing missing information and uncertainty. In this paper, a general class of neuron models accepting heterogeneous inputs in the form of mixtures of continuous (crisp and/or fuzzy) and discrete quantities admitting missing data is presented. From these, several particular models can be derived as instances and different neural architectures constructed with them. Such models deal in a natural way with problems for which information is imprecise or even missing. Their possibilities in classification and diagnostic problems are here illustrated by experiments with data from a real-world domain in the field of environmental studies. These experiments show that such neurons can both learn and classify complex data very effectively in the presence of uncertain information.Peer ReviewedPostprint (author's final draft

    Toward the automated assessment of entity-relationship diagrams

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    The need to interpret imprecise diagrams (those with malformed, missing or extraneous features) occurs in the automated assessment of diagrams. We outline our proposal for an architecture to enable the interpretation of imprecise diagrams. We discuss our preliminary work on an assessment tool, developed within this architecture, for automatically grading answers to a computer architecture examination question. Early indications are that performance is similar to that of human markers. We will be using Entity-Relationship Diagrams (ERDs) as the primary application area for our investigation of automated assessment. This paper will detail our reasons for choosing this area and outline the work ahead

    High-resolution optical and SAR image fusion for building database updating

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    This paper addresses the issue of cartographic database (DB) creation or updating using high-resolution synthetic aperture radar and optical images. In cartographic applications, objects of interest are mainly buildings and roads. This paper proposes a processing chain to create or update building DBs. The approach is composed of two steps. First, if a DB is available, the presence of each DB object is checked in the images. Then, we verify if objects coming from an image segmentation should be included in the DB. To do those two steps, relevant features are extracted from images in the neighborhood of the considered object. The object removal/inclusion in the DB is based on a score obtained by the fusion of features in the framework of Dempster–Shafer evidence theory

    The affective notes of represented space as motors of emotional and sensorial response

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    The following essay proposes to investigate the perceptual and emotional aspects related to the visualization of architectural images. The field of research is limited to a well-defined category: figurative representations as the photographic and digital images of contemporary architecture. In particular, two types will be analysed: the un-built architecture produced by Studio MIR and Bloomimages compared with the photographed built architecture. Using figurative images as a tool of reading, the aim of this work is to identify and classify three types of affective spaces capable of generating a specific kind of perception, producing a sensorial classification of atmosphere for architecture. The study of the Psychology of Art, as well as Aesthetics and Neuroaesthetics can be a valuable tool in understanding the phenomena of the present, considering the marked pictoriality of these images. The application of the analytic methodology, developed in these disciplines, can suggest a new way of "looking" at the project, paying attention to the representation of the atmospheres, which characterizes the experience of felt space
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