Introduction to algorithms
Fast multiresolution image querying
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Photobook: content-based manipulation of image databases
International Journal of Computer Vision
Wavelet-based image indexing techniques with partial sketch retrieval capability
IEEE ADL '97 Proceedings of the IEEE international forum on Research and technology advances in digital libraries
IRM: integrated region matching for image retrieval
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Similarity Searching in Medical Image Databases
IEEE Transactions on Knowledge and Data Engineering
Windsurf: Region-Based Image Retrieval Using Wavelets
DEXA '99 Proceedings of the 10th International Workshop on Database & Expert Systems Applications
FOCUS: Searching for Multi-colored Objects in a Diverse Image Database
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Image Segmentation Using Local Variation
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Psychovisually-based multiresolution image segmentation
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 3 - Volume 3
System for screening objectionable images
Computer Communications
Classify By Representative Or Associations (CBROA): a hybrid approach for image classification
MDM '05 Proceedings of the 6th international workshop on Multimedia data mining: mining integrated media and complex data
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Image retrieval based on content from digital libraries, multimedia databases, the Internet, and other sources has been an important problem addressed by several researchers. In this regard, one cannot overestimate the use of appropriate features such as color, texture, and shape. It has also become increasingly evident that the decomposition of images into regions is critical for useful results.In this paper we further study region-based image retrieval. We argue that a relationship between regions (such as a tiger amongst yellowish-green grass, or a plane against the blue sky with mountains in the background) is also important. Our local segmentation algorithm is used to detect regions a priori. Further, while searching for a match for an 'object' in the database, we allow for probabilistic 'multiple matches,' which are later pruned based on global consistent information. We provide a simple, fast algorithm implemented as an internet thin client connecting to a web server. Experimental results indicate that our method has high precision, is robust towards translation, rotation, and scale changes, can handle partial occlusion, as well as many popular image transformations (such as shear and blur) much the way humans can.