C4.5: programs for machine learning
C4.5: programs for machine learning
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
The nature of statistical learning theory
The nature of statistical learning theory
Photobook: content-based manipulation of image databases
International Journal of Computer Vision
VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
An automatic hierarchical image classification scheme
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
MPEG-7 Descriptors in Content-Based Image Retrieval with PicSOM System
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
Semantics-Based Image Retrieval by Region Saliency
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
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
Image retrieval with embedded region relationships
Proceedings of the 2003 ACM symposium on Applied computing
Semantic-meaningful content-based image retrieval in wavelet domain
MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
A Study of Shape-Based Image Retrieval
ICDCSW '04 Proceedings of the 24th International Conference on Distributed Computing Systems Workshops - W7: EC (ICDCSW'04) - Volume 7
A data mining approach to modeling relationships among categories in image collection
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Robust Feature Matching Across Widely Separated Color Images
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
A New Method for Image Classification by Using Multilevel Association Rules
ICDEW '05 Proceedings of the 21st International Conference on Data Engineering Workshops
Support vector machines for histogram-based image classification
IEEE Transactions on Neural Networks
Efficient content-based video retrieval by mining temporal patterns
Proceedings of the 9th International Workshop on Multimedia Data Mining: held in conjunction with the ACM SIGKDD 2008
Effective content-based video retrieval using pattern-indexing and matching techniques
Expert Systems with Applications: An International Journal
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Image classification has been an interesting research issue in multimedia content analysis due to the wide applications. In this paper, we observe that images can be classified (or annotated) in two ways: i) Classify by some main object, ii) Classify by multiple objects with their relations. These two types of images usually exist concurrently in real-life image databases. Although a number of image classification methods have been propose, they can only handle one certain type of images well and fail to deal with both types of images correctly at the same time. In this paper, we propose a hybrid image classification method, namely "CBROA" (Classify By Representative Or Associations), that can effectively classify both types of images at the same time. CBROA integrates the decision tree and association rules mining method in an adaptive manner with construction of a virtual semantic ontology. Experimental results show that CBROA outperforms other classification methods in terms of classification accuracy in classifying mixed types of images.