{"type":"ScholarlyArticle","title":"Fuzzy Conceptual Graphs for Matching Images of Natural Scenes","authors":[{"name":"Philippe Mulhem","slug":"philippe-mulhem","given":"Philippe","family":"Mulhem","affiliation":""},{"name":"Wee Kheng Leow","slug":"wee-kheng-leow","given":"Wee Kheng","family":"Leow","affiliation":""},{"name":"Yoong Keok Lee","slug":"yoong-keok-lee","given":"Yoong Keok","family":"Lee","affiliation":""}],"abstract":"Conceptual graphs are very useful for representing structured knowledge. However, existing formulations of fuzzy conceptual graphs are not suitable for matching images of natural scenes. This paper presents a new variation of fuzzy conceptual graphs that is more suited to image matching. This variant differentiates between a model graph that describes a known scene and an image graph which describes an input image. A new measurement is defined to measure how well a model graph matches an image graph. A fuzzy graph matching algorithm is developed based on error-tolerant subgraph isomorphism. Test results show that the matching algorithm gives very good results for matching images to predefined scene models","doi":null,"url":"https://ijcai.org/proceedings/2001/184","pdf":"https://ijcai.org/proceedings/2001/0184.pdf","markdown":"https://ijcai.org/proceedings/2001/184.md","bibtex":"https://ijcai.org/proceedings/2001/bibtex/184","volume":{"slug":"2001","title":"Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2001","url":"https://ijcai.org/proceedings/2001/","year":2001,"location":"Seattle, Washington, USA","dates":"","editors":"","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":184,"pages":{"first":1397,"last":1403},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}