Automated Measurement of Geometric Features in Curvilinear Structures Exploiting Steger's Algorithm

Accurately assessing the geometric features of curvilinear structures on images is of paramount importance in many vision-based measurement systems targeting technological fields such as quality control, defect analysis, biomedical, aerial, and satellite imaging. This paper aims at laying the basis...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2023-04, Vol.23 (8), p.4023
Main Authors: Giulietti, Nicola, Chiariotti, Paolo, Revel, Gian Marco
Format: Article
Language:English
Subjects:
Algorithms
Asymmetry
Automation
geometric feature measurement
Gravitational waves
line width measurement
Measurement
Measuring instruments
Medical imaging equipment
Quality control
Satellite imagery
Satellite imaging
Sensors
Steger algorithm
Technology application
vision-based measurement
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Summary:Accurately assessing the geometric features of curvilinear structures on images is of paramount importance in many vision-based measurement systems targeting technological fields such as quality control, defect analysis, biomedical, aerial, and satellite imaging. This paper aims at laying the basis for the development of fully automated vision-based measurement systems targeting the measurement of elements that can be treated as curvilinear structures in the resulting image, such as cracks in concrete elements. In particular, the goal is to overcome the limitation of exploiting the well-known Steger's ridge detection algorithm in these applications because of the manual identification of the input parameters characterizing the algorithm, which are preventing its extensive use in the measurement field. This paper proposes an approach to make the selection phase of these input parameters fully automated. The metrological performance of the proposed approach is discussed. The method is demonstrated on both synthesized and experimental data.
ISSN:1424-8220
1424-8220
DOI:10.3390/s23084023