Figure 2. Block Diagram of the Automatic Grading Algorithm.

After preprocessing, the algorithm delineates or segments lissamine green staining in the image. Next, the cyan and yellow channels (of the CMYK color space) are separated out from the image and the mean cyan and mean yellow intensities over the conjunctiva are calculated. The 2 mean values are used as 2 additional image features by the algorithm to describe each image. Finally, the percent staining, mean cyan, and mean yellow features are concatenated together to form a 3-dimensional feature vector for each image. The algorithm uses these feature vectors and manual gradings from a training data set to train a random forest regression, which is used to produce the automatic grading for each image.