Abstract
The subject for extracting road information automatically from map images has been regarded as effectual means to construct GIS. Until today, many different methods /approaches on this subject have been reported, but it is not easy to extract road information successfully because various kinds of map elements are overlayed and intersected. This paper addresses an advanced approach to identify road information on the basis of cooperative inference mechanism. This mechanism generates hypotheses for un-extracted roads simultaneously and interprets them. Namely, roads, disjointed by the existences of other map elements or not extracted as road fragments, are connected as a result of checking up the conformity, consistency and adequacy among hypotheses or the adjustment between hypotheses and other map elements.
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© 1997 Springer-Verlag Berlin Heidelberg
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Nishijima, M., Watanabe, T. (1997). A cooperative inference mechanism for extracting road information automatically. In: Chin, R., Pong, TC. (eds) Computer Vision — ACCV'98. ACCV 1998. Lecture Notes in Computer Science, vol 1352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63931-4_218
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DOI: https://doi.org/10.1007/3-540-63931-4_218
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