In order to find the image with the closest match, a linear search
algorithm is performed on the learning data set. For each image in
the learning data set, the Euclidean distance is calculated. After the
linear search algorithm has examined each image, the result of the
algorithm will be the image with the shortest Euclidean distance to
the test image. The concentration of the image with the shortest
Euclidean distance is the predicted concentration of the test image