A method to automatically select locally appropriate scales for feature detection, proposed by Lindeberg [8], [9], involves choosing a so-called γ-parameter. The implications of the choice of γ-parameter are studied and it is demonstrated that different values of γ can lead to qualitatively different features being detected. As an example the range of γ-values is determined such that a second derivative of Gaussian filter kernel detects ridges but not edges. Some results of this relatively simple ridge detector are shown for two-dimensional images.
CITATION STYLE
Majer, P. (2001). The influence of the γ-parameter on feature detection with automatic scale selection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2106, pp. 245–254). Springer Verlag. https://doi.org/10.1007/3-540-47778-0_21
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