Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/78157
Title: Fuzzy conceptual graphs for matching images of natural scenes
Authors: Mulhem, P.
Leow, W.K. 
Lee, Y.K.
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

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

59
checked on Dec 1, 2019

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.