A simple but powerful heuristic method for generating fuzzy rules from numerical data
Fuzzy Sets and Systems
Machine Learning
A parallel algorithm for generating chain code of objects in binary images
Information Sciences—Informatics and Computer Science: An International Journal
k-means: a new generalized k-means clustering algorithm
Pattern Recognition Letters
An Introduction to Digital Image Processing With Matlab
An Introduction to Digital Image Processing With Matlab
Locality preserving clustering for image database
Proceedings of the 12th annual ACM international conference on Multimedia
Content-based multimedia information retrieval: State of the art and challenges
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
A survey of content-based image retrieval with high-level semantics
Pattern Recognition
A modified Gabor function for content based image retrieval
Pattern Recognition Letters
Multi-object image retrieval based on shape and topology
Image Communication
Engineering Applications of Artificial Intelligence
A color image segmentation approach for content-based image retrieval
Pattern Recognition
Information Sciences: an International Journal
Editorial: Data warehouse and knowledge discovery (DAWAK'05)
Data & Knowledge Engineering
Fuzzy classifier design using genetic algorithms
Pattern Recognition
Fast computation of geometric moments using a symmetric kernel
Pattern Recognition
Wavelet and curvelet moments for image classification: Application to aggregate mixture grading
Pattern Recognition Letters
Conceptual modeling rules extracting for data streams
Knowledge-Based Systems
Advanced Information Retrieval
Electronic Notes in Theoretical Computer Science (ENTCS)
Short communication: Data mining based intelligent analysis of threatening e-mail
Knowledge-Based Systems
Data mining for exploring hidden patterns between KM and its performance
Knowledge-Based Systems
Rule extraction from trained support vector machines
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Image Retrieval With Relevance Feedback Based on Graph-Theoretic Region Correspondence Estimation
IEEE Transactions on Multimedia
On the efficient evaluation of probabilistic similarity functions for image retrieval
IEEE Transactions on Information Theory
Cascade ARTMAP: integrating neural computation and symbolic knowledge processing
IEEE Transactions on Neural Networks
Trademark image retrieval using an integrated shape descriptor
Expert Systems with Applications: An International Journal
Self organizing natural scene image retrieval
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
This paper introduces unsupervised image retrieval framework based on a rule base system. The proposed framework makes use of geometric moments (GMs) for features extraction. The main advantage with the GMs is that image coordinate transformations can be easily expressed and analyzed in terms of the corresponding transformations in the moment space. These features are used to perform the image mining for acquiring clustering knowledge from a large empirical images database. Irrelevance between images of the same cluster is precisely considered in the proposed framework through a relevant feedback phase followed by a novel clustering refinement model. The images and their corresponding classes pass to a rule base algorithm for extracting a set of accurate rules. These rules are pruning and may reduce the dimensionality of the extracted features. The advantage of the proposed framework is reflected in the retrieval process, which is limited to the images in the class of rule matched with the query image features. Experiments show that the proposed model achieves a very good performance in terms of the average precision, recall and retrieval time compared with other models.