Proceedings - International Conference on Image Processing · 2007 · 33 citations · 17 references
ComputingComputer ScienceComputer VisionDigital ImagingInformation RetrievalFeature DescriptionImage Feature EngineeringImage RegistrationImage RetrievalShape AnalysisShape RepresentationContent-based Image RetrievalFourier DescriptorsShape Feature ExtractionShape FeaturesShape RecognitionShape RetrievalTranslation InvarianceZernike Polynomials
Shape-based image description is an important approach to content-based image retrieval (CBIR). A variety of techniques are reported in the literature that aim to represent objects based on their shapes; each of these techniques has its advantages and disadvantages. Fourier descriptor (FD), a simple yet powerful technique, has attractive properties such as rotational, scale, and translational invariance. In this paper we investigate this technique and present a novel shape registration method for extracting Fourier descriptors. When evaluated against curvature scale space (CSS) and Zernike moments (ZM) in shape-based image retrieval, the proposed technique exhibits superior performance.
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Visual pattern recognition by moment invariants
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