Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mastering Data Mining: The Art and Science of Customer Relationship Management
Mastering Data Mining: The Art and Science of Customer Relationship Management
Unsupervised Feature Selection Applied to Content-Based Retrieval of Lung Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Framework for Benchmarking in CBIR
Multimedia Tools and Applications
An extensive empirical study of feature selection metrics for text classification
The Journal of Machine Learning Research
IEEE Transactions on Knowledge and Data Engineering
Visual guided navigation for image retrieval
Pattern Recognition
Rotation-invariant and scale-invariant Gabor features for texture image retrieval
Image and Vision Computing
Image indexing and retrieval based on vector quantization
Pattern Recognition
Knowledge-based image retrieval system
Knowledge-Based Systems
Features for image retrieval: an experimental comparison
Information Retrieval
Feature selection based-on genetic algorithm for image annotation
Knowledge-Based Systems
Advanced Information Retrieval
Electronic Notes in Theoretical Computer Science (ENTCS)
Embedded lattices tree: An efficient indexing scheme for content based retrieval on image databases
Journal of Visual Communication and Image Representation
A smart content-based image retrieval system based on color and texture feature
Image and Vision Computing
Learning to rank with document ranks and scores
Knowledge-Based Systems
Journal of Computer and System Sciences
A novel business cycle surveillance system using the query logs of search engines
Knowledge-Based Systems
Incremental learning of complete linear discriminant analysis for face recognition
Knowledge-Based Systems
Face recognition using discriminant sparsity neighborhood preserving embedding
Knowledge-Based Systems
Integrating wavelets with clustering and indexing for effective content-based image retrieval
Knowledge-Based Systems
Genetic algorithms in feature and instance selection
Knowledge-Based Systems
Engineering Applications of Artificial Intelligence
A new matching strategy for content based image retrieval system
Applied Soft Computing
Image indexing using the color and bit pattern feature fusion
Journal of Visual Communication and Image Representation
Feature subset selection using improved binary gravitational search algorithm
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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This paper presents a proposed model for content-based image retrieval (CBIR) which depends only on extracting the most relevant features according to a feature selection technique. The suggested feature selection technique aims at selecting the optimal features that not only maximize the detection rate but also simplify the computation of the image retrieval process. The proposed model is divided into three main techniques, the first one is concerned with the features extraction from images database, the second is performing feature discrimination, and the third is concerned with the feature selection from the original ones. As for the first technique, the 3D color histogram and the Gabor filter algorithm are used to extract the color and texture features respectively. While the second technique depends on a genetic algorithm (GA) for replacing numerical features with nominal features that represent intervals of numerical domains with discrete values. The GA is utilized in this technique to obtain the optimal boundaries of these intervals, and consequently to reduce the complexity in feature space. In the third technique, the feature selection performs two successive functions which are called preliminary and deeply reduction for extracting the most relevant features from the original features set. Indeed, the main contribution of the proposed model is providing a precise image retrieval in a short time.