Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Automatic image annotation and retrieval using cross-media relevance models
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Content-based image classification using a neural network
Pattern Recognition Letters
A bootstrapping framework for annotating and retrieving WWW images
Proceedings of the 12th annual ACM international conference on Multimedia
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 12 - Volume 12
MMM '05 Proceedings of the 11th International Multimedia Modelling Conference
Random Subwindows for Robust Image Classification
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Using One-Class and Two-Class SVMs for Multiclass Image Annotation
IEEE Transactions on Knowledge and Data Engineering
Image annotations by combining multiple evidence & wordNet
Proceedings of the 13th annual ACM international conference on Multimedia
Content-based multimedia information retrieval: State of the art and challenges
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Image annotation refinement using random walk with restarts
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Incorporating multiple SVMs for automatic image annotation
Pattern Recognition
A survey of content-based image retrieval with high-level semantics
Pattern Recognition
Web image annotation by fusing visual features and textual information
Proceedings of the 2007 ACM symposium on Applied computing
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image annotation: which approach for realistic databases?
Proceedings of the 6th ACM international conference on Image and video retrieval
Enhancing image annotation by integrating concept ontology and text-based bayesian learning model
Proceedings of the 15th international conference on Multimedia
Web Image Annotation Based on the Decision Rules Inferred by the Statistical Analysis of Web Pages
CIT '07 Proceedings of the 7th IEEE International Conference on Computer and Information Technology
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Scalable Markov model-based image annotation
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Learning to reduce the semantic gap in web image retrieval and annotation
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Real-Time Computerized Annotation of Pictures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Semantic Annotation of Real-World Web Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Categorization of Image Regions Using Dominant Color Based Vector Quantization
DICTA '08 Proceedings of the 2008 Digital Image Computing: Techniques and Applications
A fusion neural network classifier for image classification
Pattern Recognition Letters
Semantic Image Retrieval Using Region Based Inverted File
DICTA '09 Proceedings of the 2009 Digital Image Computing: Techniques and Applications
A review on automatic image annotation techniques
Pattern Recognition
Automated image annotation using global features and robust nonparametric density estimation
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Region based color image retrieval using curvelet transform
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Rotation Invariant Curvelet Features for Region Based Image Retrieval
International Journal of Computer Vision
Color Image Segmentation Based on Mean Shift and Normalized Cuts
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Image classification for content-based indexing
IEEE Transactions on Image Processing
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Support vector machines for histogram-based image classification
IEEE Transactions on Neural Networks
Fast K-means algorithm based on a level histogram for image retrieval
Expert Systems with Applications: An International Journal
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Image retrieval has lagged far behind text retrieval despite more than two decades of intensive research effort. Most of the research on image retrieval in the last two decades are on content based image retrieval or image retrieval based on low level features. Recent research in this area focuses on semantic image retrieval using automatic image annotation. Most semantic image retrieval techniques in literature, however, treat an image as a bag of features/words while ignore the structural or spatial information in the image. In this paper, we propose a structural image retrieval method based on automatic image annotation and region based inverted file. In the proposed system, regions in an image are treated the same way as keywords in a structural text document, semantic concepts are learnt from image data to label image regions as keywords and weight is assigned to each keyword according to spatial position and relationship. As the result, images are indexed and retrieved in the same way as structural document retrieval. Specifically, images are broken down to regions which are represented using colour, texture and shape features. Region features are then quantized to create visual dictionaries which are similar to monolingual dictionaries like English or Chinese dictionaries. In the next step, a semantic dictionary similar to a bilingual dictionary like the English-Chinese dictionary is learnt to mapping image regions to semantic concepts. Finally, images are then indexed and retrieved using a novel region based inverted file data structure. Results show the proposed method has significant advantage over the widely used Bayesian annotation models.