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

Volume

2

fYear

1993

fDate

26-30 Jul 1993

Firstpage

965

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/IROS.1993.583267

Filename

583267