###### Abstract  
Strabismus is a common vision disease that brings about unpleasant influence on vision, as well as life quality. A timely diagnosis is crucial for the proper treatment of strabismus. In contrast to manual evaluation, well-designed automatic evaluation can significantly improve the objectivity, reliability, and efficiency of strabismus diagnosis. In this study, we have proposed an innovative intelligent evaluation system of strabismus in digital videos, based on the cover test. In particular, the video is recorded using an infrared camera, while the subject performs automated cover tests. The video is then fed into the proposed algorithm that consists of six stages: (1) eye region extraction, (2) iris boundary detection, (3) key frame detection, (4) pupil localization, (5) deviation calculation, and (6) evaluation of strabismus. A database containing cover test data of both strabismic subjects and normal subjects was established for experiments. Experimental results demonstrate that the deviation of strabismus can be well-evaluated by our proposed method. The accuracy was over 91%, in the horizontal direction, with an error of 8 diopters; and it was over 86% in the vertical direction, with an error of 4 diopters. intelligent evaluation; automated cover tests; deviation of strabismus; pupil localization 2019 9 731 10.3390/app9040731 10.3390/app9040731 10.  
self-confidence [7, 8], which brings adverse impact on a person's life, including education, employment, and social communication [9, 10, 11, 12, 13, 14]. Thus, timely quantitative evaluation of strabismus is essential, in order to get a suitable treatment for strabismus. More specifically, accurate measurement of the deviation in strabismus is crucial in planning surgery and other treatments. Currently, several tests need to be performed, usually, to diagnose strabismus in a clinical context [15]. For example, the corneal light reflex is conducted by directly observing the displacement of the reflected image of light from the center of the pupil. Maddox rod is a technique that utilizes filters and distorting lenses for quantifying eye turns. Another way to detect and measure an eye turn is to conduct a cover test, which is the most commonly used technique. All these methods require conduction and interpretation by the clinician or ophthalmologist, which is subjective to some extent. Taking the cover test as an example, the cover procedures and assessments are conducted manually, in the existing clinical systems, and well-trained specialists are needed for the test. Therefore, this limits the effect of strabismus assessment in two aspects [16, 17]. With respect to cover procedure, the cover is given manually, so the covering time and speed of occluder movement depend on the experience of the examiners and can change from time to time. These variations of the cover may influence the assessment results. With respect to assessment, the response of subject is evaluated subjectively, which leads to more uncertainties and limitations in the final assessment. First, the direction of eye movement, the decision of whether or not moving and the responding speed for recovery, rely on the observation and determination of the examiners. The variances of assessment results, among examiners, cannot be avoided. Second, the strabismus angle has to be measured with the aid of a prism, in a separate step and by trial-and-error. This strings out the diagnosis process. Being aware of these clinical disadvantages, researchers are trying to find novel ways to improve the process of strabismus assessment. With the development of computer technology, image acquisition technology, etc., researchers have made some efforts to utilize new technologies and resources to aid ophthalmology diagnostics. Here, we give a brief review on the tools and methodologies that support the detection and diagnosis of strabismus. These methods can be summarized into two categories, namely the image-based or video-based method, and the eye-tracking based method.