DocumentCode :
1564365
Title :
A fuzzy logic CBIR system
Author :
Chiu, Chih-Yi ; Lin, Hsin-Chih ; Shi-Nine Yang
Author_Institution :
Dept. of Comput. Sci., Nat. Tsing Hua Univ., Hsinchu, Taiwan
Volume :
2
fYear :
2003
Firstpage :
1171
Abstract :
A fuzzy logic framework is proposed to alleviate two problems in traditional CBIR systems, including the semantic gap and the perception subjectivity. The proposed framework consists of two major parts, including (1) model construction and (2) query comparison. In the model construction part, fuzzy linguistic terms with associated fuzzy membership functions are automatically generated through an unsupervised fuzzy clustering algorithm. The linguistic terms provide a nature way of expressing user´s concepts, and the membership functions characterize the mapping between image features and human visual concepts. We also define the syntax and semantics rules of a query description language to unify the query expression of textual descriptions, visual examples, and relevance feedbacks. In the query comparison part, a similarity function is inferred based on user´s feedbacks to measure the similarity between the query and each image in the database. The user´s preference is also captured and retained in his/her own profile to achieve personalization. Our work provides a unified and comprehensive framework for incorporation a fuzzy approach into CBIR systems. To verify our CBIR framework, we select Tamura features to describe and retrieve texture images. Experimental results show that the proposed framework is indeed effective to alleviate the semantic gap and the perception subjectivity problems.
Keywords :
content-based retrieval; fuzzy logic; image matching; image retrieval; image texture; information retrieval systems; query processing; visual databases; CBIR systems; Tamura features; content based information retrieval; fuzzy approach; fuzzy linguistic terms; fuzzy logic; fuzzy membership functions; human visual concepts; image database; image mapping; model construction; perception subjectivity; personalization; query comparison; query description language; query textual descriptions; retrieved texture image; semantic gap; semantic rules; unsupervised fuzzy clustering algorithm; visual examples; Clustering algorithms; Computer science; Feedback; Fuzzy logic; Fuzzy systems; Humans; Image databases; Image retrieval; Spatial databases; Visual databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on
Print_ISBN :
0-7803-7810-5
Type :
conf
DOI :
10.1109/FUZZ.2003.1206597
Filename :
1206597
Link To Document :
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