Introduction - If you have any usage issues, please Google them yourself
Gabor wavelet transform applied to feature extraction of ophthalmic images.
We investigate a new approach for measuring ocular
refractive errors (astigmatism, near-sightedness and shortsightedness)
from images of the human eye [1]. This
approach uses Support Vector Machines (SVMs) to
analyse data features extracted from images of the eye
acquired with a technique known as Hartmann-Shack [2]
and output measures for the eye´ s refractive errors. Prior to
analysis and feature extraction an image processing stage
takes place to identify and crop the region of interest
considering domain spatial and geometrical information.
Then a set of relevant image features are extracted using
wavelet and Garbor Transforms. These features are finally
fed into a SVM module for analysis that provides a
diagnosis of refractive errors present in the ocular globe
under investigation.