Journal article
Design of steerable filters for feature detection using canny-like criteria
IEEE transactions on pattern analysis and machine intelligence, Vol.26(8), pp.1007-1019
08/2004
DOI: 10.1109/TPAMI.2004.44
PMID: 15641731
Abstract
We propose a general approach for the design of 2D feature detectors from a class of steerable functions based on the optimization of a Canny-like criterion. In contrast with previous computational designs, our approach is truly 2D and provides filters that have closed-form expressions. It also yields operators that have a better orientation selectivity than the classical gradient or Hessian-based detectors. We illustrate the method with the design of operators for edge and ridge detection. We present some experimental results that demonstrate the performance improvement of these new feature detectors. We propose computationally efficient local optimization algorithms for the estimation of feature orientation. We also introduce the notion of shape-adaptable feature detection and use it for the detection of image corners.
Details
- Title: Subtitle
- Design of steerable filters for feature detection using canny-like criteria
- Creators
- Mathews Jacob - Biomedical Imaging Group, Swiss Federal Institute of Technology Lausanne, CH-1015, Switzerland. Mathews.Jacob@ieee.orgMichael Unser
- Resource Type
- Journal article
- Publication Details
- IEEE transactions on pattern analysis and machine intelligence, Vol.26(8), pp.1007-1019
- DOI
- 10.1109/TPAMI.2004.44
- PMID
- 15641731
- NLM abbreviation
- IEEE Trans Pattern Anal Mach Intell
- ISSN
- 0162-8828
- eISSN
- 1939-3539
- Publisher
- United States
- Language
- English
- Date published
- 08/2004
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology
- Record Identifier
- 9984070163302771
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