2014
DOI: 10.15579/gcsr.vol1.ch10
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Image Annotation by Moments

Abstract: The rapid growth of the Internet and multimedia information has generated a need for technical indexing and searching of multimedia information, especially in image retrieval. Image searching systems have been developed to allow searching in image databases. However, these systems are still inecient in terms of semantic image searching by textual query. To perform semantic searching, it is necessary to be able to transform the visual content of the images (colours, textures, shapes) into semantic information. … Show more

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Cited by 12 publications
(10 citation statements)
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“…Therefore, Hu presented the use of moments for image analysis and pattern recognition (Hu, 1962). Legendre moments are classical orthogonal moment which are one of widest and most commonly moments used in recognition and image analysis (Oujaoura et al, 2014).…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Therefore, Hu presented the use of moments for image analysis and pattern recognition (Hu, 1962). Legendre moments are classical orthogonal moment which are one of widest and most commonly moments used in recognition and image analysis (Oujaoura et al, 2014).…”
Section: Methodsmentioning
confidence: 99%
“…Symmetry and recursion properties of the orthogonal basis function can be exploited to speed up the computation (Oujaoura et al, 2014).…”
Section: A Legendre Momentsmentioning
confidence: 99%
“…They are computed from the Legendre polynomials. Zernike moments also have been used as features set in many applications [44], as they can represent the properties of an image with no redundancy or overlapping of information between moments. They are constructed as the mapping of an image onto a set of complex Zernike polynomials [41].…”
Section: Hand-crafted Image Descriptorsmentioning
confidence: 99%
“…The computation of Legendre moments is in general a time consuming process. In many references [30,42,41,23], their computation has been performed using closed form representations for orthogonal polynomials, and taking little care to the accuracy of the quadrature formulas used to approximate integrals. In this work, we describe a fast and stable algorithm for the computation of the orthogonal moments of an image with respect to both a continuous and a discrete inner product, based on classical recurrence relations for orthonormal polynomials.…”
Section: Introductionmentioning
confidence: 99%
“…In [38], the authors propose a CAD system for the diagnosis of breast masses in mammography images which uses Zernike moments for extracting the shape and margin properties of the masses. In [30], an image annotation system, based on different type of moments, has been developed to allow searching image databases. The experimental results showed that the annotation system coupling Legendre moments to Bayesian networks gives good results for images that are well and properly segmented.…”
Section: Introductionmentioning
confidence: 99%