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2 Fundamenta Informaticae

2 2014

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Content-based Image Retrieval using Visual Attention Point Features

Wang X.-Y., Li Y.-W., Niu P.-P., Yang H.-Y., Li D.-M.

Fundamenta Informaticae

2014

Vol. 135, nr 3

309--329

One of the challenges in the development of a content-based image indexing and retrieval application is to achieve an efficient and robust indexing scheme. Color is a fundamental image feature used in content-based image retrieval (CBIR) systems. This paper proposes a robust and effective image retrieval scheme, which is based on the weighed color histogram of visual attention points. Firstly, the fully affine invariant visual attention points are extracted from the origin color image by using the Affine-SIFT (scale-invariant feature transform) detector. Secondly, according to the color complexity measure (CCM) theory, the visual weight values for the significant visual attention points are calculated to reflect the image local variation. Then, the weighed color histogram of visual attention points is constructed. Finally, the similarity between color images is computed by using the weighed color histogram of visual attention points. Experimental results show that the proposed image retrieval is not only more accurate and efficient in retrieving the user-interested images, but also yields higher retrieval accuracy than some state-of-the-art image retrieval schemes for various test DBs.

A Robust Digital Watermarking Based on Local Complex Angular Radial Transform

Niu P.-P., Wang X.-Y., Yang H.-Y., Wang P., Wang A.-L.

Fundamenta Informaticae

2014

Vol. 135, nr 3

243--268

Geometric distortions that cause displacement between embedding and detection are usually difficult for watermark to survive. It is a challenging work to design a robust image watermarking scheme against geometric distortions, especially for local geometric distortions. Based on probability density and complex angular radial transform theory, a new image watermarking algorithm robust to geometric distortions is proposed in this paper. We firstly extract the steady image feature points by using new image feature point detector, which is based on the probability density. Then we build the affine invariant local feature regions based on probability density auto-correlation matrix. And finally, we present a new image watermarking algorithm robust to geometric distortions, in which the digital watermark is embedded into the local complex angular radial transform (CART) coefficients. Experiments results show that the proposed image watermarking is not only invisible and robust against common image processing operations, but also robust against the geometric distortions.