| DC Field | Value | Language |
|---|
| dc.contributor.author | Melnyk, Roman | |
| dc.contributor.author | Kalychak, Yurii | |
| dc.coverage.temporal | 21-25 August 2018, Lviv | |
| dc.date.accessioned | 2020-06-19T12:04:37Z | - |
| dc.date.available | 2020-06-19T12:04:37Z | - |
| dc.date.created | 2018-02-28 | |
| dc.date.issued | 2018-02-28 | |
| dc.identifier.citation | Melnyk R. Analysis of Metal Defects by Clustering the Sample and Distributed Cumulative Histogram / Roman Melnyk, Yurii Kalychak // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Львів : Lviv Politechnic Publishing House, 2018. — P. 563–567. — (Machine Vision and Pattern Recognition). | |
| dc.identifier.isbn | © Національний університет „Львівська політехніка“, 2018 | |
| dc.identifier.isbn | © Національний університет „Львівська політехніка“, 2018 | |
| dc.identifier.uri | https://ena.lpnu.ua/handle/ntb/52447 | - |
| dc.description.abstract | In this paper the clustering algorithm was used
to classify the regions of the metal sample with defects to
determine their coordinates. The informative distributed
cumulative histogram is proposed. To measure sizes and
intensity of defects the IDCH image is transformed and clustered. | |
| dc.format.extent | 563-567 | |
| dc.language.iso | en | |
| dc.publisher | Lviv Politechnic Publishing House | |
| dc.relation.ispartof | Data stream mining and processing : proceedings of the IEEE second international conference, 2018 | |
| dc.relation.uri | http://www.weco.com/surface-inspection | |
| dc.relation.uri | http://cilabs.kaist.ac.kr/research/image-analysis/defect-detection | |
| dc.subject | image intensity | |
| dc.subject | surface | |
| dc.subject | defects | |
| dc.subject | clustering | |
| dc.subject | pixel | |
| dc.subject | segmentation | |
| dc.subject | inversion | |
| dc.subject | distributed cumulative histogram | |
| dc.title | Analysis of Metal Defects by Clustering the Sample and Distributed Cumulative Histogram | |
| dc.type | Conference Abstract | |
| dc.rights.holder | © Національний університет “Львівська політехніка”, 2018 | |
| dc.contributor.affiliation | Lviv Polytechnic National University | |
| dc.format.pages | 5 | |
| dc.identifier.citationen | Melnyk R. Analysis of Metal Defects by Clustering the Sample and Distributed Cumulative Histogram / Roman Melnyk, Yurii Kalychak // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Lviv Politechnic Publishing House, 2018. — P. 563–567. — (Machine Vision and Pattern Recognition). | |
| dc.relation.references | [1] L.J. Wells, M. S. Shafae and J.A. Camelio, “Automated Surface Defect Detection Using High-Density Data,” J. Manuf. Sci. Eng., 138(7), Mar, 2016. | |
| dc.relation.references | [2] I. Ahn and Ch. Kim, "Finding Defects in Regular-Texture Images," 16th Korea-Japan Joint Workshop on Frontiers of Computer Vision, Hiroshima, Japan, pp. 478-480, Feb. 2010. | |
| dc.relation.references | [3] J. Choi and Ch. Kim, "Unsupervised Detection of Surface Defects: A Two-Step Approach," IEEE International Conference of Image Processing (ICIP), Orlando, USA, pp. 1037-1040, Sep. 2012. | |
| dc.relation.references | [4] L.A.O. Martins, F.L.C. Padua, and P.E.M. Almeida, “Automatic Detection of Surface Defects on Rolled Steel Using Computer Vision and Artificial Neural Networks IECON,” 36th Annual Conference on IEEE Industrial Electronics Society, pp. 1081-1086, 2010. | |
| dc.relation.references | [5] S. Jahanbina, A.C. Bovika, E. Perezb, and D. Nair, “Automatic Inspection of Textured Surfaces by Support Vector Machines,” [Electronic resource] Link: ttps://live.ece.utexas.edu/publications | |
| dc.relation.references | [6] Wintriss defects gallery [Electronic resource] Link: http://www.weco.com/surface-inspection | |
| dc.relation.references | [7] Defect detection of various films [Electronic resource] Link: http://cilabs.kaist.ac.kr/research/image-analysis/defect-detection | |
| dc.relation.references | [8] V.H. Pham, and B.R. Lee, “An image segmentation approach for fruit defect detection using k-means clustering and graph-based algorithm,” Vietnam Journal of Computer Science, vol. 2, iss. 1, pp. 25–33, February 2015, | |
| dc.relation.references | [9] K. Zheng, Y.-S. Chang, K.-H. Wang, and Y. Yao, “Thermographic clustering analysis for defect detection in CFRP structures,” Polymer Testing, vol. 49, pp. 73-81, February 2016. | |
| dc.relation.references | [10] R. Xu, and D. Wunsch, “Survey of clustering algorithms”, IEEE Transactions on Neural Networks, vol. 16, iss. 3, pp. 645 – 678, May 2005. | |
| dc.relation.references | [11] S. Naz, H. Majeed, and H. Irshad, “Image segmentation using fuzzy clustering: A survey,” 6th International Conference on Emerging Technologies (ICET), pp. 181 – 186, 18-19 Oct. 2010. | |
| dc.relation.references | [12] S. Thilagamani1 and N. Shanthi, “A Survey on Image Segmentation Through Clustering,” International Journal of Research and Reviews in Information Sciences, vol. 1, no. 1, pp. 14-17, March 2011. | |
| dc.relation.references | [13] Y. Yang, D. Xu, F.Nie, S. Yan, and Y. Zhuang, “Clustering Using Local Discriminant Models and Global Integration,” IEEE Transactions on Image Processing, vol. 19, iss. 10, pp. 2761 – 2773, Oct. 2010 | |
| dc.relation.referencesen | [1] L.J. Wells, M. S. Shafae and J.A. Camelio, "Automated Surface Defect Detection Using High-Density Data," J. Manuf. Sci. Eng., 138(7), Mar, 2016. | |
| dc.relation.referencesen | [2] I. Ahn and Ch. Kim, "Finding Defects in Regular-Texture Images," 16th Korea-Japan Joint Workshop on Frontiers of Computer Vision, Hiroshima, Japan, pp. 478-480, Feb. 2010. | |
| dc.relation.referencesen | [3] J. Choi and Ch. Kim, "Unsupervised Detection of Surface Defects: A Two-Step Approach," IEEE International Conference of Image Processing (ICIP), Orlando, USA, pp. 1037-1040, Sep. 2012. | |
| dc.relation.referencesen | [4] L.A.O. Martins, F.L.C. Padua, and P.E.M. Almeida, "Automatic Detection of Surface Defects on Rolled Steel Using Computer Vision and Artificial Neural Networks IECON," 36th Annual Conference on IEEE Industrial Electronics Society, pp. 1081-1086, 2010. | |
| dc.relation.referencesen | [5] S. Jahanbina, A.C. Bovika, E. Perezb, and D. Nair, "Automatic Inspection of Textured Surfaces by Support Vector Machines," [Electronic resource] Link: ttps://live.ece.utexas.edu/publications | |
| dc.relation.referencesen | [6] Wintriss defects gallery [Electronic resource] Link: http://www.weco.com/surface-inspection | |
| dc.relation.referencesen | [7] Defect detection of various films [Electronic resource] Link: http://cilabs.kaist.ac.kr/research/image-analysis/defect-detection | |
| dc.relation.referencesen | [8] V.H. Pham, and B.R. Lee, "An image segmentation approach for fruit defect detection using k-means clustering and graph-based algorithm," Vietnam Journal of Computer Science, vol. 2, iss. 1, pp. 25–33, February 2015, | |
| dc.relation.referencesen | [9] K. Zheng, Y.-S. Chang, K.-H. Wang, and Y. Yao, "Thermographic clustering analysis for defect detection in CFRP structures," Polymer Testing, vol. 49, pp. 73-81, February 2016. | |
| dc.relation.referencesen | [10] R. Xu, and D. Wunsch, "Survey of clustering algorithms", IEEE Transactions on Neural Networks, vol. 16, iss. 3, pp. 645 – 678, May 2005. | |
| dc.relation.referencesen | [11] S. Naz, H. Majeed, and H. Irshad, "Image segmentation using fuzzy clustering: A survey," 6th International Conference on Emerging Technologies (ICET), pp. 181 – 186, 18-19 Oct. 2010. | |
| dc.relation.referencesen | [12] S. Thilagamani1 and N. Shanthi, "A Survey on Image Segmentation Through Clustering," International Journal of Research and Reviews in Information Sciences, vol. 1, no. 1, pp. 14-17, March 2011. | |
| dc.relation.referencesen | [13] Y. Yang, D. Xu, F.Nie, S. Yan, and Y. Zhuang, "Clustering Using Local Discriminant Models and Global Integration," IEEE Transactions on Image Processing, vol. 19, iss. 10, pp. 2761 – 2773, Oct. 2010 | |
| dc.citation.conference | IEEE second international conference "Data stream mining and processing" | |
| dc.citation.spage | 563 | |
| dc.citation.epage | 567 | |
| dc.coverage.placename | Львів | |
| Appears in Collections: | Data stream mining and processing : proceedings of the IEEE second international conference
|
