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19 July 2013 Sparse representation for image classification by using feature dictionary
Wei Zhang, Jiaojie Li, Yupu Yang
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Proceedings Volume 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013); 88782L (2013) https://doi.org/10.1117/12.2030571
Event: Fifth International Conference on Digital Image Processing, 2013, Beijing, China
Abstract
A novel image classification method is proposed based on the sparse representation. The initial dictionary consists of the feature patches obtained through the feature extraction. The K-SVD algorithm is adopted to update the dictionary. Each dictionary is learned from the images of each category, and the images of this category can be represented sparsely over this dictionary. The classification can be achieved in terms of the projection error. Experimental results show that the proposed method achieves the comparable performance.
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Wei Zhang, Jiaojie Li, and Yupu Yang "Sparse representation for image classification by using feature dictionary", Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88782L (19 July 2013); https://doi.org/10.1117/12.2030571
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KEYWORDS
Associative arrays
Image classification
Feature extraction
Control systems
Radon
Data processing
Image retrieval
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