Fast Ray Features for Learning Irregular Shapes

We introduce a new class of image features, the Ray feature set, that consider image characteristics at distant contour points, capturing information which is difficult to represent with standard feature sets. This property allows Ray features to efficiently and robustly recognize deformable or irregular shapes, such as cells in microscopic imagery. Experiments show Ray features clearly outperform other powerful features including Haar-like features and Histograms of Oriented Gradients when applied to detecting irregularly shaped neuron nuclei and mitochondria. Ray features can also provide important complementary information to Haar features for other tasks such as face detection, reducing the number of weak learners and computational cost.


Published in:
2009 IEEE 12Th International Conference On Computer Vision (ICCV), 397-404
Presented at:
12th IEEE International Conference on Computer Vision, Kyoto, JAPAN, Sep 29-Oct 02, 2009
Year:
2009
Publisher:
Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa
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 Record created 2011-12-16, last modified 2018-03-17

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