REVIEW ON FRUIT DISEASE DETECTION USING IMAGE PROCESSING

Fruit disease causes lot of economic loss and major loss in agricultural production all over the world. The crops are affected by uneven climatic conditions. Because of that diseases on plant is increased and agriculture yield is decreased[1]. Now days, the conditions become worst because of bacterial diseases. Increasing population burdens farmers to increase yield.Modern agriculture will overcome this type of effect and improves agriculture[1][4]. So,the image processing technique is used to identify the disease during its growing stage .At that time we may make some prevention to the other fruits in the field. Several methods in image processing can be used to overcome the disease[3].K-means clustering technique which is used for segmentation of image, some sort of segmented image will get extracted,some image will be finalized by using Multi-class Support vector machine[2][3]. The image which is enhanced where the segmentation is done using k-means and thresholding based segmentation where the extraction of disease in done. Discrete Wavelet Transform method extracts a set of visual features of diseased portions. Based on the extracted featuresset, a SVM classifier identifies the affected disease type and the another system which uses two database, one is for already stored image and another for query of image[6]. Web based system which is used to identify the disease of fruit for non experts, based on picture which will be represented by the symptoms of fruit[5].