Abstract
We describe a method for labelling image structure based on non-linear scale-orientation signatures which can be used as a basis for robust pixel classification. The effect of normalisation of the signatures is discussed as a means to improve classification robustness with respect to grey-level variations. In addition, model data selection and scale normalisation are investigated as a means to improve the robustness of detection with respect to the scale of structures.
Cite
CITATION STYLE
Zwiggelaar, R., Taylor, C. J., & Rubin, C. M. E. (1999). Detection of the central mass of spiculated lesions - Signature normalisation and model data aspects. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1613, pp. 406–411). Springer Verlag. https://doi.org/10.1007/3-540-48714-x_37
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