Visual information retrieval
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching and retrieval based on the vocabulary and grammar of color patterns
IEEE Transactions on Image Processing
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In this study, we propose a fuzzy logic CBIR system for textures, named LinStar Texture (i.e., Linguistic Star for Textures). The proposed system consists of two major phases, including database creation and query comparison. In the database creation phase, six Tamura features are extracted to describe each texture image in the database. A term set on each Tamura feature is generated through a fuzzy clustering algorithm so that degrees of appearance for the feature can be interpreted as five linguistic terms. In the query comparison phase, a user can pose textual descriptions or visual examples to find the desired textures. Furthermore, the query can be expressed as a logic composition of linguistic terms or Tamura feature values. The final similarity is then computed by aggregating each individual similarity through min-max composition rules. Experimental results reveal the proposed system is indeed effective. The retrieved images are perceptually satisfactory. The retrieval time is very fast.