@article{oai:mie-u.repo.nii.ac.jp:00008223,
 author = {池内, 崇 and IKEUCHI, Takashi and 小森, 照元 and KOMORI, Terumoto and 野村, 由司彦 and NOMURA, Yoshihiko and 松井, 博和 and MATSUI, Hirokazu and 加藤, 典彦 and KATO, Norihiko},
 issue = {656},
 journal = {日本機械学會論文集. C編},
 month = {Apr},
 note = {application/pdf, 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.},
 pages = {1092--1098},
 title = {計測データ誤差に基づくベイズ事後確率の伝搬誤差の解析 : 機械力学,計測,自動制御},
 volume = {76},
 year = {2001}
}