Eye diseases are burning diseases nowadays. Eye illness identification is one of the basic issues in computer vision. Three such diseases have been considered in this paper, cataract, conjunctivitis, and stye. A cataract occurs once protein builds up within the lens of an eye and makes it cloudy which prompts the decrease in vision. Conjunctivitis or pink eye is a condition where the conjunctiva of the eye inflamed by an infection or by an allergic reaction. And the third sort of illness i.e. stye is an infection that causes a young red., painful lump near the edges of the eyelid. Generally., an eye doctor uses a slit lamp camera to find these sicknesses. But because of lack of specialist eye doctor and slit lamp camera in rural areas are the main problem of the belated in detecting those diseases. In this paper first, the captured eye images collected from different patients and processed for improvement. Then HOG used for detection of the feature vector. Finally recognition of disease done with the assistance of minimum distance classifier. This planned method is economical., computationally quick and price very low. The proposed system result with average accuracy is 96.5 percent in classification. © 2017 IEEE.