2001 Volume 67 Issue 656 Pages 1092-1098
Bayesian estimation is often applied in pattern recognition problems. We formulate estimation errors of a posteriori Bayesian probabilities to be propagated from observation. Next, we apply the scheme of the formulation to a practical image recognition problem : based on a posteriori probabilities, sectionalized regions in outdoor-scene images are classified into five categories of landform elements, i, e., asphalt, concrete, sand/soil, gravel, and grass. The errors originate from RGB pixel values, and propagate to the a posteriori probabilities via intermediary HIS color measures within a region. We concretely clarify a mechanism of the propagation for all steps, and show an effectiveness of the scheme by adducing changeovers between a posteriori probabilities with two kinds of landform elements.
Transactions of the Society of Mechanical Engineers
Transactions of the Japan Society of Mechanical Engineers
Transactions of the Japan Society of Mechanical Engineers Series A
Transactions of the Japan Society of Mechanical Engineers Series B
TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C
TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series B
TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series A
