Fibrovascular redness grading using Gaussian process regression with radial basis function kernel

Information obtained from redness grading can assist clinician for diagnosis and in making clinical decision. This research work aims to mimic human perception of fibrovascular redness using features extracted from color entropy. Gaussian process regression with the radial basis function kernel has been employed to fuse relevant features and established the model of redness perception. In this paper, we present the results of the radial basis function kernel incorporated as the covariance function in the GPR as the scale, sigma is varied.