Title :
Relational fuzzy model: A representation for object identification
Author :
Shieh, John Shunen
Author_Institution :
Dept. of Comput. Sci., Memorial Univ. of Newfoundland, St. John´´s, Nfld., Canada
Abstract :
An intelligent vision system needs to identify objects that are presented in a scene. Some of the basic problems related to object identification are addressed. A new object representation scheme, the relational fuzzy model (RFM), is described. It inherits the advantages of the approaches of relational models and of recognition by parts. Fuzzy values and hedges are used to describe deformed geons that form the primitive parts of the representation. Based on the RFM representation, the structural complexity of an object and the structural similarity between objects are analyzed and measured. These fuzzy measurements aid in the identification of objects. An identification strategy used by a fuzzy knowledge-based vision system is also briefly described
Keywords :
object recognition; deformed geons; fuzzy knowledge-based vision system; fuzzy values; hedges; intelligent vision system; object identification; primitive parts; relational fuzzy model; structural complexity; structural similarity; Automatic logic units; Computer science; Fuzzy sets; Intelligent robots; Intelligent systems; Layout; Machine vision; Noise measurement; Prototypes; Taxonomy;
Conference_Titel :
Intelligent Robots and Systems '93, IROS '93. Proceedings of the 1993 IEEE/RSJ International Conference on
Conference_Location :
Yokohama
Print_ISBN :
0-7803-0823-9
DOI :
10.1109/IROS.1993.583267