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- W2044678423 abstract "Content-based image retrieval (CBIR) technique retrieves relevant images based on extracted features from image contents. Latent semantic indexing (LSI) is used as a semantic model in the CBIR field. This paper investigates the capability of LSI-based CBIR in dealing with different types of image noise, and the impact of noise on the retrieval results. To construct the feature-image matrix (FIM) in the proposed LSI framework, three wavelet-based methods are used to extract texture feature: Gabor wavelet, Daubechies wavelet, and wavelet moments. The performance of the proposed system is evaluated by a predefined accuracy measure. The results show that the LSI-based CBIR achieves a high level of accuracy with the original image database, and still performs very well in dealing with different types of image noise." @default.
- W2044678423 created "2016-06-24" @default.
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- W2044678423 date "2014-10-01" @default.
- W2044678423 modified "2023-10-16" @default.
- W2044678423 title "The effectiveness of LSI-based CBIR with image noise using wavelet-based texture" @default.
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- W2044678423 doi "https://doi.org/10.1109/ipta.2014.7001969" @default.
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