The Areal Feature Parameters

Blateyron, François

doi:10.1007/978-3-642-36458-7_3

Cited by 37 publications

(44 citation statements)

References 16 publications

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“…[50,51], and a range of case studies illustrating their use are given in Ref. [50,51], and a range of case studies illustrating their use are given in Ref.…”

Section: Areal Parametersmentioning

confidence: 99%

“…Such parameters, and in particular, profile parameters, were developed primarily to monitor the production process. A more thorough treatment of feature parameters can be found elsewhere [51]. We do not usually see field parameter values but patterns of features, such as hills and valleys, and the relationships between them [7].…”

Section: Feature Characterisationmentioning

confidence: 99%

“…A useful way to organise the relationships between critical points in hills and dales, and still retain relevant information, is that of the change tree [49,51]. The change tree represents the relationships between contour lines from a surface.…”

Section: Change Treementioning

confidence: 99%

See 2 more Smart Citations

Surface Topography Characterisation

Leach¹

2014

Fundamental Principles of Engineering Nanometrology

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“…[50,51], and a range of case studies illustrating their use are given in Ref. [50,51], and a range of case studies illustrating their use are given in Ref.…”

Section: Areal Parametersmentioning

confidence: 99%

Section: Feature Characterisationmentioning

confidence: 99%

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Surface Topography Characterisation

Leach¹

2014

Fundamental Principles of Engineering Nanometrology

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“…Several data processing techniques are available for this purpose, many being the subject of active research (for example, see [24]). For the specific test case involving micro-embossing topographies, a simple morphological segmentation into dales, as defined in ISO 25178-2 [3], [25], is perfectly adequate, as the tiles are essentially shaped as dales. The result of segmentation is shown in Figure 4.…”

Section: Processing the Tessellated Surface With The Art Shape Descrimentioning

confidence: 99%

Shape descriptors and statistical classification on areal topography data for tile inspection in tessellated surfaces

2017

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Verification of conformance to design specifications in production, and identification of defects related to wear or other damage during maintenance, are key metrological aspects that must be addressed for micro-scale tessellated surfaces. A new algorithmic approach is presented that operates on topography datasets as obtained by areal topography instruments. The approach combines segmentation algorithms with a novel implementation of the angular radial transform, originally adopted by the MPEG-7 standard, to implement shape descriptors and associated similarity metrics. Applications to the inspection and verification of laser-manufactured micro-embossing topographies are illustrated. The topographies are first segmented to extract the individual tiles; the tiles are then encoded through shape descriptors. Principal component analysis and cluster analysis are used to investigate the behaviour of the angular radial transform coefficients. Finally, an algorithmic classifier based on supervised learning (k-nearest neighbours) is implemented and shown to be effective at identifying defects and at discriminating between defect types.

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“…ISO 25178-2 only recommends one method to partition the surface, morphological segmentation. In morphological segmentation the topography is partitioned into topologically connected hills or dales [11,28,29]. After segmentation is done, parameters can be computed that capture the properties of such hills or dales; these are known as ISO feature parameters [7].…”

Section: Iso Morphological Segmentation and Feature Parametersmentioning

confidence: 99%

Review of feature boundary identification techniques for the characterization of tessellated surfaces

MacAulay

Senin

Giusca

et al. 2015

Surf. Topogr.: Metrol. Prop.

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Tessellated surfaces are structured surfaces where the dominant features are organised in periodic patterns. Tessellated surfaces are becoming increasingly popular for a wide variety of industrial uses. However, their uptake is hindered by a lack of suitable metrological techniques to categorise and verify their properties. Areal surface texture parameters, commonly used for characterisation of surface texture, may not provide relevant information for characterising the periodicity and the other functionally relevant geometric attributes of the pattern. A possible solution, recently proposed in the literature, is to directly retrieve the individual features of the pattern and to determine their relevant geometric and dimensional properties. To achieve such a characterisation it is necessary to segment the surface in order to extract the pattern units (tiles) and the individual features contained within, so that their properties can be assessed. This paper reviews a number of different techniques and compares their ability to accurately identify the tile features and their boundaries. This ability is important as it has a direct impact on the computation of dimensional and geometric properties of the features.

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The Areal Feature Parameters

Cited by 37 publications

References 16 publications

Surface Topography Characterisation

Surface Topography Characterisation

Shape descriptors and statistical classification on areal topography data for tile inspection in tessellated surfaces

Review of feature boundary identification techniques for the characterization of tessellated surfaces

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