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This data comes from a set of images of country roads in Massachusetts  Each instance represents a x   grid of pixels described by three color and four texture features  The classes are road roadline gravel grass dirt foliage trunk sky tree and sky There are instances in this data set and an attribute values are missing The frequency distribution The labeling procedure for this domain was the same as of classes is shown in Table for the scene segmentation domain Figure shows an original image on the left and its corresponding segmentation by the NKBG algorithmon the right  which is used by a human to create training labels  It is clear from this example that the regions produced by the seg mentation algonthm are noisy in nature  for example locating all of the tree trunk on the right of the image using the regions produced by the NKGB algorithm is impossible In our experiments we introduced the following confusions foliage sky gravel dirt grass dirt road gravel grass foliage sky sky tree foliage and foliage trunk sky tree 5. These confusions were suggested by Bruce Draper, who is the creator of the database.