Design Of Steerable Filters For The Detection Of Micro-Particles

This paper presents two contributions. We first introduce a continuous-domain version of Principal-Component Analysis (PCA) for designing steerable filters so that they best approximate a given set of image templates. We exploit the fact that steerability does not need to be enforced explicitly if one extends the set of templates by incorporating all their rotations. Our results extend previous work by Perona to multiple templates. We then apply our framework to the automatic detection and classification of micro-particles that carry biochemical probes for molecular diagnostics. Our continuous-domain PCA formalism is particularly well adapted in this context because the geometry of the carriers is known analytically. In addition, the steerable structure of our filters allows for a fast FFT-based recognition of the type of probe.


Published in:
2013 IEEE 10th International Symposium On Biomedical Imaging (ISBI), 934-937
Presented at:
IEEE 10th International Symposium on Biomedical Imaging - From Nano to Macro (ISBI), San Francisco, CA, APR 07-11, 2013
Year:
2013
Publisher:
New York, IEEE
ISBN:
978-1-4673-6455-3
Keywords:
Laboratories:




 Record created 2014-01-09, last modified 2018-03-17

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