Abstract: Method, apparatus, and computer program product are provided. The method includes computing a first difference image for a first eye region based on a difference of red pixel intensity and green pixel intensity of each of a first set of pixels associated with the first eye region. The method further includes determining a first eye color defect region by computing a neighborhood processed first difference image by processing the first difference image, computing a first central point of the neighborhood processed first difference image based on a weighted centroid of red pixels associated with the neighborhood processed first difference image, and thereafter computing the first eye color defect region based on the first central point, and the red pixels associated with the first difference image.

Abstract: Various methods for clustering images of faces are provided. One example method may include receiving a plurality of input clusters including a first cluster and at least a second cluster, where each input cluster including at least one feature that was extracted from an image. The example method may further include determining a first medoid for the first cluster and a second medoid for the second cluster, determining an inter-cluster distance between the first medoid and the second medoid, and merging the first cluster with the second cluster to generate a merged cluster in an instance in which the inter-cluster distance is less than a distance threshold. Similar and related example methods, example apparatuses, and example computer program products are also provided.

Abstract: Method, apparatus, and computer program product are provided. The method includes computing a first difference image for a first eye region based on a difference of red pixel intensity and green pixel intensity of each of a first set of pixels associated with the first eye region. The method further includes determining a first eye color defect region by computing a neighborhood processed first difference image by processing the first difference image, computing a first central point of the neighborhood processed first difference image based on a weighted centroid of red pixels associated with the neighborhood processed first difference image, and thereafter computing the first eye color defect region based on the first central point, and the red pixels associated with the first difference image.