Multiscale Fourier descriptor for shape-based image retrieval

Kunttu, Iivari; Lepistö, Leena; Rauhamaa, J.; Visa, Ari

doi:10.1109/icpr.2004.1334371

Cited by 45 publications

(34 citation statements)

References 12 publications

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“…More research has recently focused on multipleresolution techniques to improve accuracy and robustness in response to the influences of noise and occlusion [12][13][14]. Thourn, Kitjaidure and Kondo proposed a new multi-resolution technique in the spatial domain called the multi-level of barycentre contour [12], which can reduce noises caused by deformation and distortion.…”

Section: Mei and Androutsosmentioning

confidence: 99%

Genetic Algorithm-based Affine Parameter Estimation for Shape Recognition

Mao

Wang

et al. 2014

International Journal of Advanced Robotic Systems

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Shape recognition is a classically difficult problem because of the affine transformation between two shapes. The current study proposes an affine parameter estimation method for shape recognition based on a genetic algorithm (GA). The contributions of this study are focused on the extraction of affineinvariant features, the individual encoding scheme, and the fitness function construction policy for a GA. First, the affine-invariant characteristics of the centroid distance ratios (CDRs) of any two opposite contour points to the barycentre are analysed. Using different intervals along the azimuth angle, the different numbers of CDRs of two candidate shapes are computed as representations of the shapes, respectively. Then, the CDRs are selected based on predesigned affine parameters to construct the fitness function. After that, a GA is used to search for the affine parameters with optimal matching between candidate shapes, which serve as actual descriptions of the affine transformation between the shapes. Finally, the CDRs are resampled based on the estimated parameters to evaluate the similarity of the shapes for classification. The experimental results demonstrate the robust performance of the proposed method in shape recognition with translation, scaling, rotation and distortion.

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Section: Mei and Androutsosmentioning

confidence: 99%

Genetic Algorithm-based Affine Parameter Estimation for Shape Recognition

Mao

Wang

et al. 2014

International Journal of Advanced Robotic Systems

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“…ZM is effective for face and MPEG-7 database.GF is effective for face and fingerprint database but weak for MPEG-7 shape database. They achieved best retrieval rate for each database combining both the technique.Atul Sajjanhar, Guojun Lu et al [1], has performed image retrieval using generic fourier descriptor on MPEG-7 still images Content set and found effective retrieval efficiency.In this paper we apply fourier transform [11] for the retrieval of different medicinal plants. In addition to shape representation, texture features are also used for content based medicinal plant image retrieval.…”

Section: Literature Surveymentioning

confidence: 99%

“…Fourier descriptors are invariant to translation, scaling, rotation and change of start point. It is found that the Fourier descriptor with brightness gave a better performance than the usual fourier descriptor.Iivari Kunttu,Leena Lepisto et al [11], has made a comparison between Fourier-based descriptor, multiscale fourier descriptor and (CSS) Curvature Scale Space, for shape characterization in CBIRl. Fourier descriptor is combined with wavelet transform.…”

Section: Literature Surveymentioning

confidence: 99%

Suitability of Shape and Texture Features in Retrieval of Medicinal Plants’ Images in Indian Context

Anami¹,

Nandyal²,

Govardhan³

2012

IJMLC

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“…This can be made based on polar coordinates of a shape 6 or by Fourier transforming the wavelet coefficients obtained from the complex-valued boundary function. 7 On the other hand, when WDs are formed using several scales, the resulting feature vector is typically high dimensional due to spatial information caused by multiple scales.…”

Section: Introductionmentioning

confidence: 99%

Efficient Fourier shape descriptor for industrial defect images using wavelets

2005

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Abstract. The use of image retrieval and classification has several applications in industrial imaging systems, which typically use large image archives. In these applications, the matter of computational efficiency is essential and therefore compact visual descriptors are necessary to describe image content. A novel approach to contour-based shape description using wavelet transform combined with Fourier transform is presented. The proposed method outperforms ordinary Fourier descriptors in the retrieval of complicated industrial shapes without increasing descriptor dimensionality.

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Multiscale Fourier descriptor for shape-based image retrieval

Cited by 45 publications

References 12 publications

Genetic Algorithm-based Affine Parameter Estimation for Shape Recognition

Genetic Algorithm-based Affine Parameter Estimation for Shape Recognition

Suitability of Shape and Texture Features in Retrieval of Medicinal Plants’ Images in Indian Context

Efficient Fourier shape descriptor for industrial defect images using wavelets

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