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.
Ray features can be efficiently precomputed to reduce cost,
just as precomputing integral images reduces the overall cost of Haar features.
While Rays are slightly more expensive to precompute, t...