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|Title:||Fuzzy conceptual graphs for matching images of natural scenes||Authors:||Mulhem, P.
|Issue Date:||2001||Citation:||Mulhem, P.,Leow, W.K.,Lee, Y.K. (2001). Fuzzy conceptual graphs for matching images of natural scenes. IJCAI International Joint Conference on Artificial Intelligence : 1397-1402. ScholarBank@NUS Repository.||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.||Source Title:||IJCAI International Joint Conference on Artificial Intelligence||URI:||http://scholarbank.nus.edu.sg/handle/10635/78157||ISSN:||10450823|
|Appears in Collections:||Staff Publications|
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