Abstract
To measure the hardness of a material, an indenter is pressed into the material and the deformation is measured. As we focus on Vickers hardness testing, our exercise is to compute the diagonal lengths of a square indentation. We especially investigate if it is possible to reconstruct the shape of the indentation by the use of the Shape-from-Focus method. We show that the shape information alone does not contain enough information for a robust segmentation. However, we incorporate the depth information into an effective existing approach and achieve significantly better results.
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Gadermayr, M., Uhl, A.: Dual-resolution active contours segmentation of Vickers indentation images. In: Proceedings of the 5th International Conference on Image and Signal Processing, ICISP 2012 (2012)
Gadermayr, M., Maier, A., Uhl, A.: Algorithms for microindentation measurement in automated Vickers hardness testing. In: Tenth International Conference on Quality Control for Artificial Vision (QCAV 2011). Proceedings of SPIE, vol. 8000, pp. 80000M–1–80000M–40. SPIE, St. Etienne (2011)
Maier, A., Uhl, A.: Robust automatic indentation localisation and size approximation for vickers microindentation hardness indentations. In: Proceedings of the 7th International Symposium on Image and Signal Processing (ISPA 2011), Dubrovnik, Croatia, pp. 295–300 (September 2011)
Nayar, S.K.: Shape from focus system. In: Computer vision and pattern recognition, Proceedings CVPR 1992, pp. 302–308 (1992)
Harada, T.: Robust method for position measurement of vertex of polyhedron using shape from focus. Journal of Advanced Mechanical Design, Systems and Manufacturing 4(2), 492–503 (2010)
Osher, S., Sethian, J.A.: Fronts propagating with curvature-dependent speed: Algorithms based on hamilton-jacobi formulations. Journal of Computational Physics 79(1), 12–49 (1988)
Cremers, D., Rousson, M., Deriche, R.: A review of statistical approaches to level set segmentation: integrating color, texture, motion and shape. International Journal of Computer Vision 72(2), 195–215 (2006)
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Gadermayr, M., Uhl, A. (2012). Image Segmentation of Vickers Indentations Using Shape from Focus. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2012. Lecture Notes in Computer Science, vol 7324. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31295-3_18
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DOI: https://doi.org/10.1007/978-3-642-31295-3_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31294-6
Online ISBN: 978-3-642-31295-3
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