A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance evaluation in content-based image retrieval: overview and proposals
Pattern Recognition Letters - Special issue on image/video indexing and retrieval
Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Feature Selection Applied to Content-Based Retrieval of Lung Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Similarity for Texture Image Retrieval
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
Texture Features and Learning Similarity
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Interactive Learning with a "Society of Models"
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
NeTra: a toolbox for navigating large image databases
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
First Course On Fuzzy Theory And Applications.
First Course On Fuzzy Theory And Applications.
Dominant local binary patterns for texture classification
IEEE Transactions on Image Processing
Rotation-Invariant Texture Image Retrieval Using Rotated Complex Wavelet Filters
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Image Processing
New Media Cloud Computing: Opportunities and Challenges
International Journal of Cloud Applications and Computing
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There is no single best representation of images that can separate different classes with well defined boundaries in the feature space. Therefore, content-based image retrieval (CBIR) using conventional distance metric is not efficient in the low level image feature space viz. texture. Classifier based retrieval approaches (classification followed by retrieval) classify the query image and retrieve images only from the identified class. The performance of such approaches greatly relies on the performance of classifier. For each correct classification of query image, these systems yield high retrieval accuracy and for each misclassification the systems result in complete failure. It results huge variance in performance. This paper proposes a novel approach to content-based image retrieval called ''Class Membership-based Retrieval'' that addresses the limitations of both conventional distance based and conventional classifier based retrieval approaches. The proposed method consists of two steps. First, the class label and fuzzy class membership of query image is computed using neural network. In the second step, the retrieval is performed using a combination of simple and weighted (class membership based) distance metric in complete search space unlike the conventional classifier based retrieval techniques. The proposed technique also provides flexibility in reducing the search space in steps increasing the speed of retrieval at the cost of gradual reduction in accuracy. The performance of the method is evaluated using three texture data sets varying in orientations, complexity and number of classes. Experimental results support the proposed technique favorably when compared with other promising texture retrieval schemes.