Personal Satellite Services. Second International ICST Confernce, PSATS 2010, Rome, Italy, February 2010 Revised Selected Papers

Research Article

Semi-automatic Objects Recognition Process Based on Fuzzy Logic

Download
472 downloads
  • @INPROCEEDINGS{10.1007/978-3-642-13618-4_26,
        author={Federico Prandi and Raffaella Brumana},
        title={Semi-automatic Objects Recognition Process Based on Fuzzy Logic},
        proceedings={Personal Satellite Services. Second International ICST Confernce, PSATS 2010, Rome, Italy, February 2010 Revised Selected Papers},
        proceedings_a={PSATS},
        year={2012},
        month={5},
        keywords={Objects Recognition DSM Fuzzy logic disaster management},
        doi={10.1007/978-3-642-13618-4_26}
    }
    
  • Federico Prandi
    Raffaella Brumana
    Year: 2012
    Semi-automatic Objects Recognition Process Based on Fuzzy Logic
    PSATS
    Springer
    DOI: 10.1007/978-3-642-13618-4_26
Federico Prandi1,*, Raffaella Brumana1,*
  • 1: Politecnico di Milano
*Contact email: federico.prandi@polimi.it, raffaella.brumana@polimi.it

Abstract

Three dimensional object extraction and recognition (OER) from geographic data has been one of most important topics in photogrammetry for a long time. Today, the capability of being able to rapidly generate high-density DSM increases the provision of geographic information. However the discrete nature of the measuring makes it more difficult to correctly recognize and extract 3D objects from these surfaces. The proposed methodology wants to semi-automate some of the operations required for clustering of geographic objects, in order to perform the recognition process. Fuzzy logic allows using, in a mathematical process the uncertain information typical of human reasoning. In this paper we present an approach for detecting objects based on fuzzy logic. In a first phase only the structural information are extracted and integrated in the fuzzy reasoning process in order to have a more generic treatment. The recognition algorithm has been tested with different data sets and different objectives.