POMEGRANATE FRUIT DISEASES DETECTION USING IMAGE PROCESSING TECHNIQUES: A REVIEW

Abstract

The Agriculture plant diseases are responsible for farmer economic losses. These diseases affect on plant root, fruit, leaf, and stem. Detection of disease at early stages helps the farmer to improve productivity. In the traditional system agriculture experts and experienced farmer can recognize the plant diseases at the lower accuracy which causes losses to farmers. Currently several researchers are proposing soft computing and expert systems to recognize plant diseases.  Plant disease identification by visual way is less accurate because some diseases do not have any visible symptoms or some of the diseases appear too late at the time of harvesting. The modern technology in agriculture sector can substantially improve the agriculture production & sustainability. This paper provides a review for fruit disease detection techniques for pomegranate plants. This study includes preprocessing, segmentation, feature extraction and classification techniques for pomegranate fruit diseases detection systems. This paper also states the comparison and limitations of existing fruit disease detection techniques.