19 July 2013 Sparse representation for image classification by using feature dictionary
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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.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wei Zhang, Wei Zhang, Jiaojie Li, Jiaojie Li, Yupu Yang, 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); doi: 10.1117/12.2030571; https://doi.org/10.1117/12.2030571
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