Abstract
This paper presents a fast multispectral texture defect detection method based on the underlying three-dimensional spatial probabilistic image model. The model first adaptively learns its parameters on the flawless texture part and subsequently checks for texture defects using the recursive prediction analysis. We provide colour textile defect detection results that indicate the advantages of the proposed method. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Haindl, M., Grim, J., & Mikeš, S. (2007). Texture defect detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4673 LNCS, pp. 987–994). Springer Verlag. https://doi.org/10.1007/978-3-540-74272-2_122
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