Associative Document Retrieval Techniques Using Bibliographic Information
Journal of the ACM (JACM)
A vector space model for automatic indexing
Communications of the ACM
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Unsupervised Categorization for Image Database Overview
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
Integrating wavelets with clustering and indexing for effective content-based image retrieval
Knowledge-Based Systems
A new automatic identification system of insect images at the order level
Knowledge-Based Systems
Policy-enhanced ANFIS model to counter SOAP-related attacks
Knowledge-Based Systems
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This article proposes an automatic characterization method by comparing unknown images with examples more or less known. Our approach allows to use uncertain examples but easy to obtain (e.g. by automatic retrieval on the Internet). The use of fuzzy logic and adaptive clustering makes it possible to reduce automatically the noise from this database by preserving only the examples having a strong level of redundancy in the dominant shapes. To validate this method, we compared our artificial process of recognition with the estimation of human operators. The tests show that the automatic process gives an average accuracy of the characterization near to 95%.