The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
An efficient implementation of a scaling minimum-cost flow algorithm
Journal of Algorithms
Multidimensional access methods
ACM Computing Surveys (CSUR)
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 2)
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Managing gigabytes (2nd ed.): compressing and indexing documents and images
IRM: integrated region matching for image retrieval
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
On “shapes” of colors for content-based image retrieval
MULTIMEDIA '00 Proceedings of the 2000 ACM workshops on Multimedia
ACM Computing Surveys (CSUR)
Modern Information Retrieval
Similarity Search without Tears: The OMNI Family of All-purpose Access Methods
Proceedings of the 17th International Conference on Data Engineering
M-tree: An Efficient Access Method for Similarity Search in Metric Spaces
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
IDEAS '01 Proceedings of the International Database Engineering & Applications Symposium
Blobworld: A System for Region-Based Image Indexing and Retrieval
VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
Content-Based Image Retrieval over the Web Using Query by Sketch and Relevance Feedback
VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
A compact and efficient image retrieval approach based on border/interior pixel classification
Proceedings of the eleventh international conference on Information and knowledge management
Unbalanced region matching based on two-level description for image retrieval
Pattern Recognition Letters
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Recently, several content-based image retrieval (CBIR) systems that make use of segmented images have been proposed. In these systems, images are segmented and represented as a set of regions, and the distance between images is computed according to the visual features of their regions. A major problem of existing distance functions used to compare segmented images is that they are not metrics. Hence, it is not possible to exploit filtering techniques and/or access methods to speedup query processing, as both techniques make extensive use of the triangular inequality property - one of the metric axioms. In this work, we propose MiCROM (Minimum-Cost Region Matching), an effective metric distance which models the comparison of segmented images as a minimum-cost network flow problem. To our knowledge, this is the first time a true metric distance function is proposed to evaluate the distance between segmented images. Our experiments show that MiCROM is at least as effective as existing non-metric distances. Moreover, we have been able to use the recently proposed Omni-sequential filtering technique, and have achieved nearly 2/3 savings in retrieval/query processing time.