A FORTRAN subroutine for cartographic generalization

Wolf, Gert W.

doi:10.1016/0098-3004(91)90002-u

Cited by 36 publications

(21 citation statements)

References 5 publications

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“…With this approach, a surface is considered as a stochastic or deterministic assembly of different scale features. Pattern recognition techniques such as "edge recognition" and "Wolf pruning" [19] are utilized to carry out topology analysis. These methods provide a stable approach for extracting features of functional interest by accurately excluding insignificant geometrical features that are induced, such as measurement noise.…”

Section: Five Steps To a Feature Parametermentioning

confidence: 99%

Numerical characterisation of biomedical titanium surface texture using novel feature parameters

Wang

Jiang

Gurdak

et al. 2011

Wear

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In biomedicine, titanium materials with specific surface textures (for example, those produced using consecutive polishing, sandblasting and acid etching) are widely used to facilitate osseointegration of human/animal tissue with implant surface structures. The surface texture has a critical role on the material"s functionality in terms of cellular adhesion and proliferation. However, conventional surface topography characterisation parameters pertinent to cellular attachment such as Sds (density of summits of a surface) and Ssc (arithmetic mean summit curvature of a surface) are liable to be influenced by low amplitude high spatial frequency components or measurement noise. In this research, a novel feature characterisation, based on pattern recognition techniques is implemented on specially processed titanium surfaces. The mean dimensions and densities of the micro-scale features of the surfaces are extracted. The statistical analysis results demonstrate the efficiency and stability of the feature analysis compared to the use of conventional surface texture parameters. Additionally, potentially efficient parameters for characterisation of biomedical surfaces are indicated through the use of a one-way analysis of variance. As a case study, from the point of view of surface metrology, limited experimental data is presented; the intention of the authors is to give a guide to innovative use of the novel surface characterisation techniques. A large amount of biomedical experiments would be needed in the future to fully validate the correlation between the surface texture parameters and its biomedical functions but the present work provides a useful start point for a larger study.

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Section: Five Steps To a Feature Parametermentioning

confidence: 99%

Numerical characterisation of biomedical titanium surface texture using novel feature parameters

Wang

Jiang

Gurdak

et al. 2011

Wear

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“…This group of parameters uses novel pattern recognition techniques which ensure that targeted surface features could be examined verisimilarly [41][42][43]. In addition, from material and tribological aspects, the feature parameters are normally considered being highly functional relevance and stable to target surface [41,55].…”

Section: Discussionmentioning

confidence: 99%

“…These parameters have some limitations. Innovatively defined feature parameters apply statistics to a subset of predefined topographic features which are usually extracted using the pattern recognition techniques such as the "hill and valley detection" [41], "edge detection" [54] and "Wolf pruning" [43]. Some feature parameter applications in engineering disciplines have shown their significant advantageous [41,54,55].…”

Section: Surface Characterisationmentioning

confidence: 99%

“…The feature parameters carry out statistics to a subset of predefined topographic features. Some pattern recognition techniques such as the "hill and valley recognition", "edge detection" and "Wolf prune" are involved so that the surface features can be characterised using these parameters [41][42][43]. By means of the advanced surface characterisation techniques [42,44], comprehensive surface topographies of wear particles can be investigated for wear analysis and OA diagnostics.…”

Section: Introductionmentioning

confidence: 99%

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A new approach to numerical characterisation of wear particle surfaces in three-dimensions for wear study

Tian

Wang

Peng

et al. 2012

Wear

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In the wear and tear process of synovial joints, wear particles generated and released from articular cartilage within the joints have different surface topology and mechanical property. Three-dimensional (3D) particle images acquired using laser scanning confocal microscopy (LSCM) contain appropriate surface information for quantitatively characterizing the surface topology and changes to seek a further understanding of the wear process and wear features. This paper presents a new attempt on the 3D numerical characterisation of wear particle surfaces using the field and feature parameter sets which are defined in ISO/FDIS 25178-2. Based on the innovative pattern recognition capability, the feature parameters are, for the first time, employed for quantitative analysis of wear debris surface textures. Through performing parameter classification, ANOVA analysis and correlation analysis, typical changing trends of the surface transformation of the wear particles along with the severity of wear conditions and Osteoarthritis (OA) have been observed. Moreover, the feature parameters have shown a significant sensitivity with the wear particle surfaces texture evolution under OA development. A correlation analysis of the numerical analysis results of cartilage surface texture variations and that of their wear particles has been conducted in this study. Key surface descriptors have been determined. Further research is needed to verify the above outcomes using clinic samples.

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“…About decision trees, the relationship between peaks and sinks can be traced. The ISO 25178-2 describes for this the Wolf pruning [12]. According to ISO 25178-3 [13] the limit for the pruning is specified from 5% of S z.…”

Section: Feature Parametermentioning

confidence: 99%

Description of the Pumping Rate of Shaft Counterfaces in the Sealing System Radial Lip Seal Using the 3D Parameters of ISO 25178

et al. 2016

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The sealing system radial lip seal represent a complex tribological system with high requirements to be fulfilled over a long time. The surface texture of shaft counterface has a great influence on the performance of radial lip sealing system. A usability evaluation of shaft counterface with standardized 2D roughness parameters is not possible, because they represent only limited functional properties of the shaft counterface. With optical measurement instruments, shaft counterfaces can be measured in 3D. By using 3D metrology shaft counterface data the circumferential direction can also be evaluated. Together with the 3D surface parameters according to ISO 25178 this provides a fully new approach to evaluate shaft counterface. After the measurement, the data must be preprocessed to obtain meaningful parameters and to get a uniform database regardless of the manufacturing process. Measuring the pumping rate of shaft counterfaces is a common but time-consuming method to describe the quality of radial lip seals. For the evaluation of the 3D surface parameter according to ISO 25178 correlation analyses were performed by using a linear regression analysis. The correlation analyzes have shown, that the 3D parameters have the potential to describe the quality of shaft counterfaces for sealing purpose.

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A FORTRAN subroutine for cartographic generalization

Cited by 36 publications

References 5 publications

Numerical characterisation of biomedical titanium surface texture using novel feature parameters

Numerical characterisation of biomedical titanium surface texture using novel feature parameters

A new approach to numerical characterisation of wear particle surfaces in three-dimensions for wear study

Description of the Pumping Rate of Shaft Counterfaces in the Sealing System Radial Lip Seal Using the 3D Parameters of ISO 25178

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