In this dissertation, an effort has been made to automate the cataract detection, classification and grading method. Algorithms have been developed which detect the presence of cataract. Currently, the detector enhances the image quality, and works on cropped images which depict only the region of interest i.e. the pupil in an eye image using MATLAB functions and then computes the pixel colour which are crisp (non fuzzy) numbers limited within a specific range are sent as input to a Fuzzy Inference System. Rules are designed which execute using fuzzy reasoning of membership functions. The input to an if-then rule is the current value for the input variable and the output is an entire fuzzy set . This fuzzy set is later defuzzified to obtain a crisp result assigning one value to the output which is a crisp result i.e. non-cataract or cataract and is further classified into its types. With little modification, proposed model can be used as a tool for semi-automated cataract detection and classification.