Abstract
Although several image classification methods have been proposed in the literature, most of them require an offline training phase to generate appropriate classifiers. In this paper, we show how combining MPEG-7 color descriptors can achieve an accurately image classification while bypassing the training phase. More specifically, we illustrate how the combination of Compact Color, Dominant Color and Color Layout was used to extract Global Similarity feature for input into ascending hierarchical classification. We introduce a weighting process to compute the global similarity from descriptors. Our experimental evaluation of the proposed classification method shows its significant effectiveness and high reliability.
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Jarraya, S.K., Fendri, E., Hammami, M., Ben-Abdallah, H. (2015). Combined MPEG7 Color Descriptors for Image Classification: Bypassing the Training Phase. In: Paredes, R., Cardoso, J., Pardo, X. (eds) Pattern Recognition and Image Analysis. IbPRIA 2015. Lecture Notes in Computer Science(), vol 9117. Springer, Cham. https://doi.org/10.1007/978-3-319-19390-8_82
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DOI: https://doi.org/10.1007/978-3-319-19390-8_82
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