Invariant Features for Gray Scale Images
Mustererkennung 1995, 17. DAGM-Symposium
Empirical Evaluation of Dissimilarity Measures for Color and Texture
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Impact of object extraction methods on classification performance in surface inspection systems
Machine Vision and Applications - Integrated Imaging and Vision Techniques for Industrial Inspection
Assessment of the influence of adaptive components in trainable surface inspection systems
Machine Vision and Applications - Integrated Imaging and Vision Techniques for Industrial Inspection
Invariance in kernel methods by haar-integration kernels
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
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In this paper we propose a novel method for the construction of invariant textural features for grey scale images. The textural features are based on an averaging over the 2D Euclidean transformation group with relational kernels. They are invariant against 2D Euclidean motion and strictly increasing grey scale transformations. Beside other fields of texture analysis applications we consider texture defect detection here. We provide a systematic method how to apply these grey scale features to this task. This will include the localization and classification of the defects. First experiments with real textile texture images taken from the TILDA database show promising results. They are presented in this paper.