Fuzzy mathematical approach to pattern recognition
Fuzzy mathematical approach to pattern recognition
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
Supporting similarity queries in MARS
MULTIMEDIA '97 Proceedings of the fifth ACM international conference on Multimedia
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
A Region-Based Fuzzy Feature Matching Approach to Content-Based Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Blobworld: A System for Region-Based Image Indexing and Retrieval
VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
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
Content-Based Image Retrieval Based on a Fuzzy Approach
IEEE Transactions on Knowledge and Data Engineering
Color texture measurement and segmentation
Signal Processing - Special section on content-based image and video retrieval
Efficient compressed domain target image search and retrieval
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Texture classification and segmentation using wavelet frames
IEEE Transactions on Image Processing
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This paper proposes a region based approach for image retrieval. We develop an algorithm to segment an image into fuzzy regions based on coefficients of multiscale wavelet packet transform. The wavelet based features are clustered using fuzzy C-means algorithm. The final cluster centroids which are the representative points, signify the color and texture properties of the preassigned number of classes. Fuzzy Topological relationships are computed from the final fuzzy partition matrix. The color and texture properties as indicated by centroids and spatial relations between the segmented regions are used together to provide overall characterization of an image. The closeness between two images are estimated from these properties. The performance of the system is demonstrated using different set of examples from general purpose image database to prove that, our algorithm can be used to generate meaningful descriptions about the contents of the images.