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The detection of leaf diseases in plants generally involves visualobservation of patterns appearing on the leaf surface. However, there are manydiseases that are distinguished based on very subtle changes in these visuallyobservable patterns. This paper attempts to identify plant leaf diseases usingimage processing techniques. The focus of this study is on the detection ofcitrus leaf canker disease. Canker is a bacterial infection of leaves. Symptomsof citrus cankers include brown spots on the leaves, often with a watery oroily appearance. The spots (called lesions in botany) are usually yellow. It issurrounded by a halo of the leaves and is found on both the top and bottom ofthe leaf. This paper describes various methods that have been used to detectcitrus leaf canker disease. The methods used are histogram comparison andk-means clustering. Using these methods, citrus canker development was detectedbased on histograms generated based on leaf patterns. The results thus obtainedcan be used, after consultation with experts in the field of agriculture, toidentify suitable treatments for the processes used.

Unified View of Damage leaves Planimetry & Analysis Using Digital Images Processing Techniques