Novel Approach for Automatic Cataract Detection Using Image Processing

Abstract

Digital image processing techniques have made a significant contribution to medical science. A cataract is one of the most common ocular diseases and the most common cause of ocular mutilation worldwide, which can result in a partial or complete loss of vision. The lens becomes blurry as a protein coating grows slowly, reducing vision, and eventually leading to blindness. Cataract diagnosis is very expensive for the poor. Early detection and treatment of cataracts is thought to be a key strategy to avoid blindness, In this framework, we create a unique approach for detecting cataracts in their early stages that is highly exact, robust, cost-effective, and convenient. The main purpose is to analyze ocular visuals in attempt to decide if an eye is healthful or compromised by cataracts. Proposed system will automatically detect conjunctivitis with next to no processing time and maximum precision. In this article, we propose an efficient technique for identifying the volume, position, and severity of cataracts immediately. The suggested methodology can also pinpoint the cataract's position. The proposed scheme has the advantage of providing high-quality grading platform for identifying cataracts and determining the dispersion percent composition between both the normal and healthy eye.