Early Recognition of Herb Sickness Using SVM

A wide range of crops are grown throughout the year in India. India is basically an agriculture need of country. Widespread farming also makes the herbs prone to a lot of sickness. There are no efficient methods to detect these sicknesses from its outset. People in the rural areas where most of the agriculture happens are totally helpless in situations where most of their crops have been affected by sickness. Most of the sicknesses of the herbs have a characteristic feature on the leaf. By applying data processing techniques like data enhancement and feature extraction, we can extract the required information. It is used to analyze the type and severity of the sickness. The obtained information when it was fed to a classifier like support vector machine (SVM), then herb can be classified with sickness. We can also determine the stages of the sickness (infant or mid or terminal). We also provide a solution as a message to the farmers from the classification algorithm by analyzing the depth of the sickness on plant with the measures of photosynthesis.