Fast multiresolution image querying
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Multidimensional co-occurrence matrices for object recognition and matching
Graphical Models and Image Processing
VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Efficient Color Histogram Indexing for Quadratic Form Distance Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Query by Visual Example - Content based Image Retrieval
EDBT '92 Proceedings of the 3rd International Conference on Extending Database Technology: Advances in Database Technology
Image Retrieval by Elastic Matching of User Sketches
ICIAP '95 Proceedings of the 8th International Conference on Image Analysis and Processing
Textures and Structural Defects
CAIP '97 Proceedings of the 7th International Conference on Computer Analysis of Images and Patterns
WebSeer: An Image Search Engine for the World Wide Web
WebSeer: An Image Search Engine for the World Wide Web
Buoy indexing of metric feature spaces for fast approximate image queries
Proceedings of the sixth Eurographics workshop on Multimedia 2001
Learning to rank for content-based image retrieval
Proceedings of the international conference on Multimedia information retrieval
Exploiting contextual information for image re-ranking
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
Exploiting contextual spaces for image re-ranking and rank aggregation
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Image re-ranking and rank aggregation based on similarity of ranked lists
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
Exploiting clustering approaches for image re-ranking
Journal of Visual Languages and Computing
Comparative study of global color and texture descriptors for web image retrieval
Journal of Visual Communication and Image Representation
A novel image retrieval approach combining multiple features of color-connected regions
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Optimising the choice of colours of an image database for dichromats
MLDM'05 Proceedings of the 4th international conference on Machine Learning and Data Mining in Pattern Recognition
Image retrieval using weighted color co-occurrence matrix
BNCOD'05 Proceedings of the 22nd British National conference on Databases: enterprise, Skills and Innovation
Mining dichromatic colours from video
ICDM'06 Proceedings of the 6th Industrial Conference on Data Mining conference on Advances in Data Mining: applications in Medicine, Web Mining, Marketing, Image and Signal Mining
Exploiting pairwise recommendation and clustering strategies for image re-ranking
Information Sciences: an International Journal
Image re-ranking and rank aggregation based on similarity of ranked lists
Pattern Recognition
Image and Vision Computing
Using contextual spaces for image re-ranking and rank aggregation
Multimedia Tools and Applications
Multimodal retrieval with relevance feedback based on genetic programming
Multimedia Tools and Applications
Hi-index | 0.01 |
Multimedia documents are different from traditional text documents, because they may contain encodings of raw sensorical data. This fact has severe consequences for the efficient indexing and retrieval of information from documents in large unstructured collections (e.g. WWW), because it is very difficult to automatically identify generic meanings from visual or audible objects.A novel method for image retrieval from large collections is proposed in this paper. The method is based on color co-occurrence descriptors that utilize compact representations of essential information of the visual image content. The set of descriptor elements represents "elementary" color segments, their borders, and their mutual spatial distribution on the image frame. Such representation is flexible enough to describe image scenes ranging from simple combinations of color segments to high frequency color textures equally well.At the retrieval stage the comparison between a given query descriptor and the database descriptors is performed by a similarity measure. Image descriptors are robust versus affine transformations and several other image distortions. The consideration of the descriptors as sets of elements allows the combination of several images or subimages into a single query.Basic properties of the method are demonstrated experimentally on an image database containing 20000 images.