Content-Based Image Retrieval at the End of the Early Years
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
Image Indexing Using Color Correlograms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
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
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Content-based retrieval of medical images by combining global features
CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories
Effective Image Retrieval Based on Hidden Concept Discovery in Image Database
IEEE Transactions on Image Processing
Extracting semantics from audio-visual content: the final frontier in multimedia retrieval
IEEE Transactions on Neural Networks
| Hi-index | 0.00 |
This paper proposes an algorithm using local energy of color correlograms without any explicit using sub-block energy of color correlograms. The sub-block energy is defined as sub-windows from color correlograms information based on color distribution of original image. The model for image annotation involves computing histogram using color correlograms and analysis its sub-block characteristics. Similarly, sub-block energy is applied to annotate image's class and got a satisfied result. The model is fast and invariant to image's size and rotation. The comparison with SVM is done by experiments demonstrate the model is quite successful in annotation of image.