Automatic evaluation of degradation of paint coatings through EM algorithm

Xavier Quintana, Elisa Martínez, Javier Melenchón

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

2 Citations (Scopus)
43 Downloads (Pure)


An unsupervised application for the visual analysis of metallic substrates and paint coatings is presented. Model based classification is used for the analysis of metallic substrates while a segmentation of the image is required to distinguish between paint and substrate or between paint and rust for the analysis of paint coatings. A unified framework based on the Expectation-Maximization (EM) algorithm is presented to solve both analyses. The EM algorithm is used both as a colour-based identification method for measuring cleanness properties of the substrate's surface, and also as a colour-based segmentation method for extracting the paint regions of the coating's surface. An initialisation method and a pre-processing step are proposed to avoid false segmentations. Experimental results on real samples show more repeatability and accuracy than the results obtained by human visual inspection. Each analysis has been visually illustrated with a representative example.

Original languageEnglish
Title of host publicationIEEE International Conference on Image Processing
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages4
ISBN (Print)9780780377508
Publication statusPublished - 14 Sept 2003
Externally publishedYes
EventProceedings: 2003 International Conference on Image Processing, ICIP-2003 - Barcelona, Spain
Duration: 14 Sept 200317 Sept 2003


ConferenceProceedings: 2003 International Conference on Image Processing, ICIP-2003


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