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Optimal steerable filters for feature detection
Conference proceeding   Open access

Optimal steerable filters for feature detection

M Jacob and M Unser
Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), Vol.3, pp.III-433
2003
DOI: 10.1109/ICIP.2003.1247274
url
https://doi.org/10.1109/ICIP.2003.1247274View
Published (Version of record) Open Access

Abstract

We present a new approach for the design of optimal steerable 2-D templates for feature detection. As opposed to classical schemes where the optimal 1-D template is derived and extended to 2-D, we directly obtain the 2-D template. We choose the template from a class of steerable functions based on the analytic optimization of a Canny-like criterion. Our approach gives more orientation selective templates that have simple closed form expression. We illustrate the method with the design of operators for edge and ridge detection and demonstrate their performance improvement in practical applications.
Jacobian matrices Computer vision Matched filters Filtering Image edge detection Design methodology Nonlinear filters Detectors Biomedical imaging Signal to noise ratio

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