Knowledge-based understanding of road maps and other line images

Ilg, Markus

doi:10.1109/icpr.1990.118113

Cited by 10 publications

(3 citation statements)

References 4 publications

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“…Presence or absence of structural primitives, mainly lines and nodes, are also important for Ebi et al (1992) and for Ilg (1990) in assessing image complexity and ability to recreate map images from automated digitizing. Mersey (1990) tried to balance the number of classes which a choropleth map portrayed with a sensible choice of colour scales.…”

Section: Measuring Graphical Complexitymentioning

confidence: 98%

Measuring Map Complexity

Fairbairn

2006

The Cartographic Journal

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In this paper, issues of complexity and their application to cartographic practice and enquiry are addressed. After an initial discussion of the nature of complexity and its fitful study in cartography over recent years, an assessment is made of the potential for quantifying map complexity. A series of practical tests was devised and is described. These consider a wide range of metrics, including spatial statistical measures, entropy and image-based indices. Their application to both raster and vector mapping is investigated. Data compression shows promise as an index which can be used to characterize the graphical variation within the map face. The nature of digital data compression is described, with reference to raster map representations, and it is determined that a data-compression ratio can act as a simple and effective complexity measure. The paper concludes by listing some of the reasons why complexity, as measured by data compression, could be used in cartographic practice.

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Section: Measuring Graphical Complexitymentioning

confidence: 98%

Measuring Map Complexity

Fairbairn

2006

The Cartographic Journal

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“…Interestingly, others have used the related notion of Voronoi tessellation for grouping [1,20], but in these approaches no special status is given to endpoints. Endpoints and the discontinuities in boundary orientation that give rise to them are critical for unit formation in human psychophysics [24].…”

Section: Proposition 4 the Midpoint Between A And B Lies In Fl(a B)mentioning

confidence: 98%

Contour Fragment Grouping and Shared, Simple Occluders

August

Siddiqi

Zucker

1999

Computer Vision and Image Understanding

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“…Dentre as diversas operações que utilizam esqueletos, podemos citar as de agrupamento (como as de análise de documentos [40]), de segmentação [10], de planejamento de trajetórias [9] e de neuromorfometria [16,20,21,41], além de descrição de forma [7,58].…”

Section: Capítulo 4 Esqueletos Multi-escala Via I Ftunclassified

Projeto de operadores de processamento e analise de imagens baseados na transformada imagem-floresta

Cunha¹,

Falcão²

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Diversos problemas em processamento e análise de imagens podem ser abordados como um problema de particionamento ótimo de uma imagem baseado em pixels sementes. A transformada imagem-floresta (I FT) se propõe a resolver tais problemas de maneira unificada e eficiente, a partir do cálculo de florestas de caminhos mínimos. Podendo ser considerada uma generalização de trabalhos voltados para a segmentação de imagens baseada em bordas, a I FT já foi utilizada para segmentação baseada em regiões, cálculo de linhas divisoras de águas e cálculo de transformadas de distância, inclusive baseadas na métrica Euclideana.Neste trabalho acrescentamos novos operadores ao contexto da I FT, como métodos de segmentação de imagens baseada em conexidade fuzzy, geração de esqueletos multiescala e operadores conexos. Realizamos comparações qualitativas e quantitativas com outros operadores descritos na literatura, além de apresentar exemplos de aplicações em imagens médicas e em vídeo digital. Exploramos também algumas questões de cunho teórico, como provas de corretude, análises de complexidades computacionais e garantias de qualidade do resultado de alguns métodos.

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Knowledge-based understanding of road maps and other line images

Cited by 10 publications

References 4 publications

Measuring Map Complexity

Measuring Map Complexity

Contour Fragment Grouping and Shared, Simple Occluders

Projeto de operadores de processamento e analise de imagens baseados na transformada imagem-floresta

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