Analysis and study of cataract detection techniques

One of the dominant causes of visual impairment worldwide is Cataract. It causes a blurred and foggy vision which can lead to partial or complete loss of eyesight. A protein layer is developed gradually and the lens becomes cloudy over a long period of time which reduces vision and leads to blindness. Early treatment can lessen the difficulties faced by cataract patients and avert visual impairment. People living in underdeveloped countries and rural areas cannot get effective treatment in time due to scarcity of eye care services and resources. Additionally, the existing methods for cataract diagnosis are sophisticated and expensive. Considering the above scenario, cutting down the cost and simplifying the process of cataract diagnosis is important. Also transportation and portability of the equipments required is an important factor while diagnosing such a catastrophic disease. The goal of this paper is to study, analyze and put forth different cataract detection methods and techniques. This paper classifies various techniques stated and implemented until now based on three basic steps: 1)Pre-processing, 2)Feature extraction, 3)Classifier construction.