Abstract
Whereas common Vickers indentation segmentation algorithms are precise with high quality images, low quality images often cannot be segmented appropriately. We investigate an approach, where unfocused images are segmented. On the one hand, the segmentation accuracy of low quality images can be improved. On the other hand we aim in reducing the overall runtime of the hardness testing method. We introduce one approach based on single unfocused images and one gradual enhancement approach based on image series.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Maier, A., Uhl, A.: Robust automatic indentation localisation and size approximation for vickers microindentation hardness indentations. In: Proc. of the 7th Intern. Symposium on Image and Signal Processing, pp. 295–300 (September 2011)
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–10. SPIE (June 2011)
Ji, Y., Xu, A.: A new method for automatically measurement of vickers hardness using thick line hough transform and least square method. In: Proceedings of the 2nd International Congress on Image and Signal Processing (CISP 2009), pp. 1–4 (2009)
Liming, W., Qu, Z., Yaohua, D., Miaoxian, Z.: Automatically analyzing the impress image of vickers hardness test using wavelet. China Mechanics Engineering 15(6) (March 2006)
Qu, Z., Guozheng, Y., Yi, Z.: A new method for quickly and automatically analysis of the image of vickers hardness using wavelet theory. Acta Metrologica Sinica 26(3), 245–248 (2005)
Macedo, M., Mendes, V.B., Conci, A., Leta, F.R.: Using hough transform as an auxiliary technique for vickers hardness measurement. In: Proceedings of the 13th International Conference on Systems, Signals and Image Processing (IWSSIP 2006), pp. 287–290 (2006)
Mendes, V., Leta, F.: Automatic measurement of Brinell and Vickers hardness using computer vision techniques. In: Proceedings of the XVII IMEKO World Congress, Dubrovnik, Croatia, pp. 992–995 (June 2003)
Sugimoto, T., Kawaguchi, T.: Development of an automatic Vickers hardness testing system using image processing technology. IEEE Transactions on Industrial Electronics 44(5), 696–702 (1997)
Yao, L., Fang, C.-H.: A hardness measuring method based on hough fuzzy vertex detection algorithm. IEEE Trans. on Industrial Electronics 53(3), 963–973 (2006)
Gadermayr, M., Uhl, A.: Dual-resolution active contours segmentation of Vickers indentation images. Intern. Conf. on Image and Signal Proc. (June 2012)
Gadermayr, M., Maier, A., Uhl, A.: A robust algorithm for automated microindentation measurement in vickers hardness testing. Journal of Electronic Imaging (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gadermayr, M., Maier, A., Uhl, A. (2012). The Impact of Unfocused Vickers Indentation Images on the Segmentation Performance. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2012. Lecture Notes in Computer Science, vol 7432. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33191-6_46
Download citation
DOI: https://doi.org/10.1007/978-3-642-33191-6_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33190-9
Online ISBN: 978-3-642-33191-6
eBook Packages: Computer ScienceComputer Science (R0)