A Qualitative Theory for Shape Representation

Museros, Lledó; Escrig, M. Teresa

doi:10.4114/ia.v8i23.801

Cited by 10 publications

(35 citation statements)

References 11 publications

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“…This approach differs from the previous works by Museros et al [9,10,11,12] in the following points: (1) the current qualitative des-cription of shape introduces a new qualitative concept for describing the edge connection and it also presents a higher granularity for the qualitative concepts angle, compared length and type of curvature, allowing to differentiate between more shapes [29]; (2) the colour of each object is described qualitatively instead of using its RGB coordinates, which is a more cognitive method; (3) the size of the objects is described qualitatively comparing it to the rest of the objects composing the mosaic, which does not limit our approach to the predefined pieces that compose the mosaic; and (4) the matching algorithm is similarity-based, instead of using all-or-nothing matching of qualitative features or RGB values,which speeds up the process.…”

Section: Introductioncontrasting

confidence: 46%

“…In the scenario of the presented approach, there is not a predefined set of recognizable tiles, each mosaic design may be composed by any number of different tiles, which differs from previous works by Museros et al [9,10,11,12], in which the set of tiles on the table must be those composing the final design.…”

Section: Comparison To Other Approachesmentioning

confidence: 64%

“…Regarding the computational time, note that the approach presented here accelerates Museros' et al [9,10,11,12] process of pick-and-place a tesserae from 3 seconds to 2.4 seconds, that is 0.6 seconds per tile. For instance, this is a reduction of 1 minute (from 8.3 min to 7.3 min) assembling a mosaic composed of 100 pieces.…”

Section: Comparison To Other Approachesmentioning

confidence: 99%

“…There are some works in the literature approaching the solution which can be classified into: (i) systems using a numerical description of the design [8]; and (ii) systems using a qualitative description of the mosaic [9,10,11,12,13,14].…”

Section: Introductionmentioning

confidence: 99%

“…These numerical data were interpreted by control software that enabled a Cartesian robot to assemble mosaic An approach for assembling mosaics by exact matching of pieces described qualitatively and RGB colour values was presented by Museros et al [9,10,11,12]. However, as some qualitative terms used in a description of shape are related to an interval of values, it can happen that two very close numerical values located on the limit of those intervals are assigned different qualitative terms.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Measures of similarity between qualitative descriptions of shape, colour and size applied to mosaic assembling

Falomir

Museros

Abril

et al. 2013

Journal of Visual Communication and Image Representation

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Versión / Versió:Pre-print AbstractA computational approach for obtaining a similarity measure between qualitative descriptions of shape, colour and size of objects within digital images is presented. According to the definition of the qualitative features, the similarity values determined are based on conceptual neighbourhood diagrams or interval distances. An approximate matching algorithm between object descriptions is defined and applied to tile mosaic assembling and results of previous approaches are improved.

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Section: Introductioncontrasting

confidence: 46%

Section: Comparison To Other Approachesmentioning

confidence: 64%

Section: Comparison To Other Approachesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Measures of similarity between qualitative descriptions of shape, colour and size applied to mosaic assembling

Falomir

Museros

Abril

et al. 2013

Journal of Visual Communication and Image Representation

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Qualitative modeling

Forbus

2010

WIRES Cognitive Science

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Qualitative modeling concerns the representations and reasoning that people use to understand continuous aspects of the world. Qualitative models formalize everyday notions of causality and provide accounts of how to ground symbolic, relational representations in perceptual processes. This article surveys the basic ideas of qualitative modeling and their applications from a cognitive science perspective. It describes the basic principles of qualitative modeling, and a variety of qualitative representations that have been developed for quantities and for relationships between them, providing a kind of qualitative mathematics. Three ontological frameworks for organizing modeling knowledge (processes, components, and field) are summarized, along with research on automatically assembling models for particular tasks from such knowledge. Qualitative simulation and how it carves up time into meaningful units is discussed. We discuss several accounts of causal reasoning about dynamical systems, based on different choices of qualitative mathematics and ontology. Qualitative spatial reasoning is explored, both in terms of relational systems and visual reasoning. Applications of qualitative models of particular interest to cognitive scientists are described, including how they have been used to capture the expertise of scientists and engineers and how they have been used in education. Open questions and frontiers are also discussed, focusing on relationships between ideas developed in the qualitative modeling community and other areas of cognitive science. WIREs Cogni Sci 2011 2 374-391 DOI: 10.1002/wcs.115 For further resources related to this article, please visit the WIREs website.

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2D qualitative shape matching applied to ceramic mosaic assembly

et al. 2011

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A theory of shape recognition of 2D objects and its application in the ceramic industry for intelligent automation of the mosaic mural assembly process are presented in this paper. This theory qualitatively describes the shapes of the objects, considering: i) shape boundary characteristics, such as angles, relative length, concavities, and curvature; and ii) their color and size. The shapes to be recognized may be regular or irregular closed polygons, or closed curvilinear figures. Each figure is described as a symbolic character string that contains all its distinctive characteristics. This description is used to determine whether the shape of two figures matches. Then, given a design of a mosaic and given a set of physical ceramic tesserae, an application is developed in order to recognize the tesserae that form the mosaic, thus enabling the intelligent and automated assembly of ceramic mosaics.

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A Qualitative Theory for Shape Representation

Cited by 10 publications

References 11 publications

Measures of similarity between qualitative descriptions of shape, colour and size applied to mosaic assembling

Measures of similarity between qualitative descriptions of shape, colour and size applied to mosaic assembling

Qualitative modeling

2D qualitative shape matching applied to ceramic mosaic assembly

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