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\section{Results and Discussion}  \subsection {Segmentation using K-Means Algorithm}  We segmented the images using the K-Means algorithm with different values of $k$. Ideally, we want a $k$ that would cluster the images such that the clusters contain either infected pixels only or healthy pixels only. For this experiment, we tried setting $k$ to 2, 3, and 4. Figure \ref{fig:kImageSegment} shows the results of the segmentation.   When $k$ is set to 2, it is expected that one cluster will contain the infected pixels and the other will contain the healthy pixels. But in our data set, most of the images cannot be separated well using just two clusters. Figure \ref{fig:kImageSegment} (Right) is an example of this. Its healthy pixels had a yellow green color while its infected pixels had parts which are dark brown and parts which are light brown, causing one cluster to mix healthy and infected pixels. Setting $k$ to 3 gives satisfactory results. Some pixels still get mixed up, specially those in the boundary of healthy and infected. Figure \ref{fig:zoomedImage} shows this slight mix up where a few green healthy pixels were grouped together with infected pixels at $k=3$. It also shows that increasing $k$ to 4 separates the green healthy pixels further from the infected cluster, giving a more precise segmentation than 3.