Automatic Interpretation of Floor Plans Usingspatial

نویسندگان

  • HANAN SAMET
  • AYA SOFFER
چکیده

A system is presented that classiies objects in raw images using statistical pattern recognition and spatial indexing. The system is given a training set containing samples of feature vectors of objects that may be found in the images. This method of classiication was applied to automatic interpretation of oor plans. A number of data structures are suggested for storing the training set. Of these, the adaptive k-d tree was found to be a highly eecient storage mechanism, and provided recognition rates of 98% and higher. Storing the training set as feature ranges per class also gave very high recognition rates, at the cost of a relatively small number of comparisons.

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تاریخ انتشار 2007