In object-oriented classification, an raster image is first segmented into coherent / homogeneous objects. The size of these objects, also called segments, can be manipulated by the interpreter using parameters such as shape and compactness and color. I this tutorial I used 0.5m resolution Arial image to classify the image in to different classes.