  India is an agriculture-dependent country. As we all know that farming is the
backbone of our country it is our responsibility to preserve the crops.
However, we cannot stop the destruction of crops by natural calamities at least
we have to try to protect our crops from diseases. To, detect a plant disease
we need a fast automatic way. So, this paper presents a model to identify the
particular disease of plant leaves at early stages so that we can prevent or
take a remedy to stop spreading of the disease. This proposed model is made
into five sessions. Image preprocessing includes the enhancement of the low
light image done using inception modules in CNN. Low-resolution image
enhancement is done using an Adversarial Neural Network. This also includes
Conversion of RGB Image to YCrCb color space. Next, this paper presents a
methodology for image segmentation which is an important aspect for identifying
the disease symptoms. This segmentation is done using the genetic algorithm.
Due to this process the segmentation of the leaf Image this helps in detection
of the leaf mage automatically and classifying. Texture extraction is done
using the statistical model called GLCM and finally, the classification of the
diseases is done using the SVM using Different Kernels with the high accuracy.
