Agricultural image processing is one of most innovative and important image processing areas recognized in last few years. Because of the vast range of associated sub domain it is having the current attention of the researchers. In this paper, the exploration of different domains associated with agricultural image processing is defined. The paper has also explored the recognition model with broader view. The paper has presented a generalized framework for plant disease classification and recognition. The paper has also defined a study on some of the effective classification approaches including SVM, Neural Network, KMeans and PCA.

Agricultural image processing is having its significance to classify the agricultural objects as well as to identify the disease. These diseases are specific to the agricultural object or generic in nature. In this paper, an effective way is defined to identify the leaf disease over the plants. The work is here defined based on moment based analysis defined under clustering improved neural network approach. The work is here improved as a layered clustered and classification approach. In first stage, the identification of disease ROI is done. This identification is done using the CMeans Clustering Approach. Once the disease ROI is identified, the next work is to perform neural network approach for disease identification. The obtained results shows the effective recognition of disease area over the leaf images.