Optimal Steerable Filters for Feature Detection

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.


Published in:
Proceedings of the 2003 IEEE International Conference on Image Processing (ICIP'03), Barcelona, Kingdom of Spain, 433–436
Year:
2003
Publisher:
IEEE
Laboratories:




 Record created 2015-09-18, last modified 2018-09-13

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