A cost model for nearest neighbor search in high-dimensional data space
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Fuzzy Database Modeling
A Region-Based Fuzzy Feature Matching Approach to Content-Based Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
FeedbackBypass: A New Approach to Interactive Similarity Query Processing
Proceedings of the 27th International Conference on Very Large Data Bases
Normalized Cuts and Image Segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A content based image retrieval system based on the fuzzy ARTMAP architecture
Proceedings of the 12th annual ACM international conference on Multimedia
Proceedings of the 6th ACM international conference on Image and video retrieval
The state of the art in image and video retrieval
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
ORF-NT: an object-based image retrieval framework using neighborhood trees
ISCIS'05 Proceedings of the 20th international conference on Computer and Information Sciences
FQAS'11 Proceedings of the 9th international conference on Flexible Query Answering Systems
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A major design issue in content-based image retrieval system is the selection of the feature set. This study attacks the problem of finding a discriminative feature for each class, which is optimal in some sense. The class-dependent feature is, then, used to calculate the membership value of each object class for content-based fuzzy image retrieval systems. The Best Representative Feature (BRF) for each class is identified in a training stage. Then, using the BRF of each object class, the segment groups in the images are labeled by the membership values of each object class. The segment groups are obtained in a greedy algorithm by minimizing the distance between each training object and the segment groups, using the BRF. This minimum distance is taken as the membership value of the training object for that particular segment group. Finally, the query object is matched to each segment group in a fuzzy database using the membership values of segment groups. The BRF is selected among the MPEG-7 descriptors. The proposed scheme yields substantially better retrieval rates compared to the available fixed feature content-based image retrieval systems.