Activity 14: Pattern Recognition

In this activity we attempted automated classification. We first extracted the mean features of each class. We then classified test objects by finding the class nearest the object in feature space. I used 4 classes:

Classes
leaf 1/leaf 2/25 centavos/flower

I used 4 features: mean red, mean green, mean blue and shape. To extract a single value for shape, I used the follow function to trace the perimeter of the object the took the ratio of its square to the area. This proved to be a valid measurement as it allowed the distinction between the two leaf classes. I used 5 objects per class to get the mean values and 2 objects per class for testing. My program was able to classify each test object (two tests per class) correctly.

I give myself a 10/10 since I was able to create a program that could classify object based on both color and shape.