In the recent past, the automatic identification of plant leaf disease and classification has plays vital role in the field of agriculture using digital image processing techniques. The high involvement of a plant is most important for both human life and natural environment balancing. The agricultural plants may highly suffer from diseases such as human beings and animals. There could be the huge number of plant diseases that may cause and affect the plant growth. Those diseases may damage entire plant including leaf and plant products. If the proper action again the disease is not taken, the entire plant may be damaged or leaf drop may occurred depends on the strength of the diseases. The digital image processing technology is incorporated with the agricultural department to utilize the technology. The digital image processing has various phases for plant leaf disease identification and classification. The preprocessing technique can be applied to remove the noses from the plant image to improve the quality of the image. The image enhancement technique is useful to improve the contrast and brightness of the image. The various segmentation techniques are applied to extract the plant disease portion from the leaf image. The various features are extracted to train the neural network for classifying as given image is normal or abnormal. This paper reviews various techniques applied on plant leaf image in various stages such as preprocessing, segmentation, feature extraction and classification.
Volume 11 | 08-Special Issue
Pages: 1463-1475