Plant Disease Diagnosis Using Distance Based Partition
Keywords:
Leaf Diseases Analysis, Clustering Segmentation, featuresAbstract
Plant disease analysis is one of the critical tasks in the field of agriculture. In this paper we define a layered model to identify the plant disease based on leaf images. To perform the disease identification and categorization there is requirement of some clustering and
classification algorithm. In this work a layered approach is suggested to perform the identification of disease in plant and to classify the collection of plant images based on the disease. The clustering is performed at the initial based on intensity variation analysis. Once the clusters are identified, the refinement over these clusters is performed using mathematical operators. image segmentation is performed to identify the diseased regions. Then, features are extracted from segmented regions using standard feature
extraction techniques. These features are then used for classification into disease type. The clustering is performed at the initial based on intensity variation analysis. Once the clusters are identified, the refinement over these clusters is performed using mathematical operators.
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