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Strabismus is a pathology that affects the parallelism between two eyes. Estimates show that 1.3% to 3.5% of children aged six months to six years have strabismus around the world. Strabismus can lead to irreversible loss of vision, so early detection and appropriate treatment increase the likelihood of alignment being restored to normal. That said, in this study we proposed an automatic evaluation system to detect strabismus in face images, analyzing the horizontal positioning of the limb center in relation to the center of the corners of the eyes. The proposed method consists of ve steps: (1) acquisition, (2) detection of the eye region, (3) segmentation and reconstruction of the sclera, (4) detection of the limb region and corners of the eyes and (5) identication of the presence of strabismus, with this approach we obtain 90.1% sensitivity, 100% specicity and 91.1% accuracy.

Automatic Ocular Alignment Evaluation for Strabismus Detection Using Index of Phylogenetic Diversity and Support Vector Machine