Joo, Hyonam2015-06-232015-06-231985http://hdl.handle.net/10919/53076Two methods of designing a point classifier are discussed in this paper, one is a binary decision tree classifier based on the Fisher's linear discriminant function as a decision rule at each nonterminal node, and the other is a contextual classifier which gives each pixel the highest probability label given some substantially sized context including the pixel. Experiments were performed both on a simulated image and real images to illustrate the improvement of the classification accuracy over the conventional single-stage Bayes classifier under Gaussian distribution assumption.vi, 93 leavesapplication/pdfen-USIn CopyrightLD5655.V855 1985.J67Pattern recognition systemsImage processing -- ExperimentsThesis