The Experts below are selected from a list of 6216 Experts worldwide ranked by ideXlab platform
Samim Konjicija - One of the best experts on this subject based on the ideXlab platform.
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Phase preserving Fourier Descriptor for shape-based image retrieval
Signal Processing: Image Communication, 2016Co-Authors: Emir Sokic, Samim KonjicijaAbstract:Shape is one of the most important discriminative elements for the content based image retrieval and the most challenging for quantification and description. Fourier Descriptors are a very efficient shape description method used in shape-based image retrieval tasks. In order to achieve invariance under rotation and starting point change, most Fourier Descriptor implementations disregard the phase of Fourier coefficients, consequently losing valuable information about the shape. This paper proposes a novel method of extracting Fourier Descriptors that preserve the phase of Fourier coefficients. We introduce specific points, called pseudomirror points, and use them as a shape orientation reference. They facilitate the extraction of phase-preserving Fourier Descriptors which are invariant under translation, scaling, rotation and starting point change. The proposed Descriptor was tested on four popular benchmarking datasets: MPEG7 CE-1 Set B, Swedish leaf, ETH-80 and Kimia99 datasets. Performance and computational complexity measures indicate that the proposed method outperforms other state-of-the-art phase-based Fourier Descriptors. In addition, it outperforms other state-of-the-art magnitude-based Fourier Descriptors, and many non-Fourier based shape description methods in terms of performance - complexity ratio. HighlightsMagnitude-based Fourier Descriptors discard information contained in phase.Invariant phase-preserving Fourier Descriptor is proposed.Pseudomirror points are introduced, and used as shape orientation references.The proposed Descriptor is compact, effective and simple to extract and compare.Retrieval performance is improved without increasing computational complexity.
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shape description using phase preserving Fourier Descriptor
International Conference on Multimedia and Expo, 2015Co-Authors: Emir Sokic, Samim KonjicijaAbstract:Contour-based Fourier Descriptors are established as a simple and effective shape description method for content-based image retrieval. In order to achieve invariance under rotation and starting point change, most Fourier Descriptor implementations disregard the phase of the Fourier coefficients. We introduce a novel method for extracting Fourier Descriptors, which preserve the phase of Fourier coefficients and have the desired invariance. We propose specific points, called pseudomirror points, to be used as shape orientation reference. Experimental results indicate that the proposed method significantly outperforms other Fourier Descriptor based techniques.
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ICME - Shape description using phase-preserving Fourier Descriptor
2015 IEEE International Conference on Multimedia and Expo (ICME), 2015Co-Authors: Emir Sokic, Samim KonjicijaAbstract:Contour-based Fourier Descriptors are established as a simple and effective shape description method for content-based image retrieval. In order to achieve invariance under rotation and starting point change, most Fourier Descriptor implementations disregard the phase of the Fourier coefficients. We introduce a novel method for extracting Fourier Descriptors, which preserve the phase of Fourier coefficients and have the desired invariance. We propose specific points, called pseudomirror points, to be used as shape orientation reference. Experimental results indicate that the proposed method significantly outperforms other Fourier Descriptor based techniques.
Dengsheng Zhang - One of the best experts on this subject based on the ideXlab platform.
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generic Fourier Descriptor for shape based image retrieval
International Conference on Multimedia and Expo, 2002Co-Authors: Dengsheng ZhangAbstract:Shape description is one of the key parts of image content description in MPEG-7. Most existing shape Descriptors are usually either application dependent or non-robust, making them undesirable for generic shape description. A generic Fourier Descriptor (GFD) is proposed to overcome the drawbacks of existing shape representation techniques. The proposed shape Descriptor is derived by applying a 2D Fourier transform on a polar raster sampled shape image. The acquired shape Descriptor is application independent and robust. Experimental results show the GFD outperforms the Zernike moment Descriptor (ZMD) which has been proposed as the shape Descriptor for MPEG-7.
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shape based image retrieval using generic Fourier Descriptor
Signal Processing-image Communication, 2002Co-Authors: Dengsheng ZhangAbstract:Shape description is one of the key parts of image content description for image retrieval. Most of the existing shape Descriptors are usually either application dependent or non-robust, making them undesirable for generic shape description. In this paper, a generic Fourier Descriptor (GFD) is proposed to overcome the drawbacks of existing shape representation techniques. The proposed shape Descriptor is derived by applying two-dimensional Fourier transform on a polar-raster sampled shape image. The acquired shape Descriptor is application independent and robust. Experimental results show that the proposed GFD outperforms common contour-based and region-based shape Descriptors.
Emir Sokic - One of the best experts on this subject based on the ideXlab platform.
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Phase preserving Fourier Descriptor for shape-based image retrieval
Signal Processing: Image Communication, 2016Co-Authors: Emir Sokic, Samim KonjicijaAbstract:Shape is one of the most important discriminative elements for the content based image retrieval and the most challenging for quantification and description. Fourier Descriptors are a very efficient shape description method used in shape-based image retrieval tasks. In order to achieve invariance under rotation and starting point change, most Fourier Descriptor implementations disregard the phase of Fourier coefficients, consequently losing valuable information about the shape. This paper proposes a novel method of extracting Fourier Descriptors that preserve the phase of Fourier coefficients. We introduce specific points, called pseudomirror points, and use them as a shape orientation reference. They facilitate the extraction of phase-preserving Fourier Descriptors which are invariant under translation, scaling, rotation and starting point change. The proposed Descriptor was tested on four popular benchmarking datasets: MPEG7 CE-1 Set B, Swedish leaf, ETH-80 and Kimia99 datasets. Performance and computational complexity measures indicate that the proposed method outperforms other state-of-the-art phase-based Fourier Descriptors. In addition, it outperforms other state-of-the-art magnitude-based Fourier Descriptors, and many non-Fourier based shape description methods in terms of performance - complexity ratio. HighlightsMagnitude-based Fourier Descriptors discard information contained in phase.Invariant phase-preserving Fourier Descriptor is proposed.Pseudomirror points are introduced, and used as shape orientation references.The proposed Descriptor is compact, effective and simple to extract and compare.Retrieval performance is improved without increasing computational complexity.
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shape description using phase preserving Fourier Descriptor
International Conference on Multimedia and Expo, 2015Co-Authors: Emir Sokic, Samim KonjicijaAbstract:Contour-based Fourier Descriptors are established as a simple and effective shape description method for content-based image retrieval. In order to achieve invariance under rotation and starting point change, most Fourier Descriptor implementations disregard the phase of the Fourier coefficients. We introduce a novel method for extracting Fourier Descriptors, which preserve the phase of Fourier coefficients and have the desired invariance. We propose specific points, called pseudomirror points, to be used as shape orientation reference. Experimental results indicate that the proposed method significantly outperforms other Fourier Descriptor based techniques.
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ICME - Shape description using phase-preserving Fourier Descriptor
2015 IEEE International Conference on Multimedia and Expo (ICME), 2015Co-Authors: Emir Sokic, Samim KonjicijaAbstract:Contour-based Fourier Descriptors are established as a simple and effective shape description method for content-based image retrieval. In order to achieve invariance under rotation and starting point change, most Fourier Descriptor implementations disregard the phase of the Fourier coefficients. We introduce a novel method for extracting Fourier Descriptors, which preserve the phase of Fourier coefficients and have the desired invariance. We propose specific points, called pseudomirror points, to be used as shape orientation reference. Experimental results indicate that the proposed method significantly outperforms other Fourier Descriptor based techniques.
Ari Visa - One of the best experts on this subject based on the ideXlab platform.
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color Fourier Descriptor for defect image retrieval
International Conference on Image Analysis and Processing, 2005Co-Authors: Iivari Kunttu, Leena Lepisto, Juhani Rauhamaa, Ari VisaAbstract:The shapes of the objects in the images are important in the content-based image retrieval systems. In the contour-based shape description, Fourier Descriptors have been proved to be effective and efficient methods. However, in addition to contour shape, Fourier description can be used to characterize also the color of the object. In this paper, we introduce new Color Fourier Descriptors. In these Descriptors, the boundary information is combined with the color of the object. The results obtained from the retrieval experiments show that by combining the color information with the boundary shape of the object, the retrieval accuracy can be clearly improved. This can be done without increasing the dimensionality of the Descriptor.
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ICIAP - Color Fourier Descriptor for defect image retrieval
Image Analysis and Processing – ICIAP 2005, 2005Co-Authors: Iivari Kunttu, Leena Lepisto, Juhani Rauhamaa, Ari VisaAbstract:The shapes of the objects in the images are important in the content-based image retrieval systems. In the contour-based shape description, Fourier Descriptors have been proved to be effective and efficient methods. However, in addition to contour shape, Fourier description can be used to characterize also the color of the object. In this paper, we introduce new Color Fourier Descriptors. In these Descriptors, the boundary information is combined with the color of the object. The results obtained from the retrieval experiments show that by combining the color information with the boundary shape of the object, the retrieval accuracy can be clearly improved. This can be done without increasing the dimensionality of the Descriptor.
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multiscale Fourier Descriptor for shape based image retrieval
International Conference on Pattern Recognition, 2004Co-Authors: Iivari Kunttu, Leena Lepisto, Juhani Rauhamaa, Ari VisaAbstract:The shapes occurring in the images are important in the content-based image retrieval. We introduce a new Fourier-based Descriptor for the characterization of the shapes for retrieval purposes. This Descriptor combines the benefits of the wavelet transform and Fourier transform. This way the Fourier Descriptors can be presented in multiple scales, which improves the shape retrieval accuracy of the commonly used Fourier-Descriptors. The multiscale Fourier Descriptor is formed by applying the complex wavelet transforms to the boundary function of an object extracted from an image. After that, the Fourier transform is applied to the wavelet coefficients in multiple scales. This way the multiscale shape representation can be expressed in a rotation invariant form. The retrieval efficiency of this multiscale Fourier Descriptor is compared to an ordinary Fourier Descriptor and CSS-shape representation.
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ICPR (2) - Multiscale Fourier Descriptor for shape-based image retrieval
2004Co-Authors: Iivari Kunttu, Leena Lepisto, Juhani Rauhamaa, Ari VisaAbstract:The shapes occurring in the images are important in the content-based image retrieval. We introduce a new Fourier-based Descriptor for the characterization of the shapes for retrieval purposes. This Descriptor combines the benefits of the wavelet transform and Fourier transform. This way the Fourier Descriptors can be presented in multiple scales, which improves the shape retrieval accuracy of the commonly used Fourier-Descriptors. The multiscale Fourier Descriptor is formed by applying the complex wavelet transforms to the boundary function of an object extracted from an image. After that, the Fourier transform is applied to the wavelet coefficients in multiple scales. This way the multiscale shape representation can be expressed in a rotation invariant form. The retrieval efficiency of this multiscale Fourier Descriptor is compared to an ordinary Fourier Descriptor and CSS-shape representation.
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multiscale Fourier Descriptor for shape classification
International Conference on Image Analysis and Processing, 2003Co-Authors: Iivari Kunttu, Leena Lepisto, Juhani Rauhamaa, Ari VisaAbstract:The description of object shape is an important characteristic of an image. In image processing and pattern recognition, several different shape Descriptors are used. In human visual perception, shapes are processed in multiple resolutions. Therefore, multiscale shape representation is essential in shape based image classification and retrieval. In the description of an object shape, the multiresolution representation provides also additional accuracy to the shape classification. We introduce a new Descriptor for shape classification. This Descriptor is called the multiscale Fourier Descriptor, and it combines the benefits of a Fourier Descriptor and multiscale shape representation. This Descriptor is formed by applying a Fourier transform to the coefficients of the wavelet transform of the object boundary. In this way, the Fourier Descriptor can be presented in multiple resolutions. We performed classification experiments using three image databases. The classification results of our method are compared to those of Fourier Descriptors.
Iivari Kunttu - One of the best experts on this subject based on the ideXlab platform.
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shape based retrieval of industrial surface defects using angular radius Fourier Descriptor
Iet Image Processing, 2007Co-Authors: Iivari Kunttu, Leena LepistoAbstract:Current industrial surface inspection systems are capable of detecting various defects and producing images of them. The defect images are collected into large image databases. Effective retrieval methods are necessary to analyse the defects stored in the database. In this work, a novel shape Descriptor for surface defect image retrieval is presented. The Descriptor is based on the Fourier transform of the defect boundary. The proposed method, angular radius Fourier Descriptor, combines the boundary function with the directional angle of the boundary line. The proposed method outperforms ordinary Fourier Descriptors in the retrieval of paper defect shapes without increasing computational cost.
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color Fourier Descriptor for defect image retrieval
International Conference on Image Analysis and Processing, 2005Co-Authors: Iivari Kunttu, Leena Lepisto, Juhani Rauhamaa, Ari VisaAbstract:The shapes of the objects in the images are important in the content-based image retrieval systems. In the contour-based shape description, Fourier Descriptors have been proved to be effective and efficient methods. However, in addition to contour shape, Fourier description can be used to characterize also the color of the object. In this paper, we introduce new Color Fourier Descriptors. In these Descriptors, the boundary information is combined with the color of the object. The results obtained from the retrieval experiments show that by combining the color information with the boundary shape of the object, the retrieval accuracy can be clearly improved. This can be done without increasing the dimensionality of the Descriptor.
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ICIAP - Color Fourier Descriptor for defect image retrieval
Image Analysis and Processing – ICIAP 2005, 2005Co-Authors: Iivari Kunttu, Leena Lepisto, Juhani Rauhamaa, Ari VisaAbstract:The shapes of the objects in the images are important in the content-based image retrieval systems. In the contour-based shape description, Fourier Descriptors have been proved to be effective and efficient methods. However, in addition to contour shape, Fourier description can be used to characterize also the color of the object. In this paper, we introduce new Color Fourier Descriptors. In these Descriptors, the boundary information is combined with the color of the object. The results obtained from the retrieval experiments show that by combining the color information with the boundary shape of the object, the retrieval accuracy can be clearly improved. This can be done without increasing the dimensionality of the Descriptor.
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multiscale Fourier Descriptor for shape based image retrieval
International Conference on Pattern Recognition, 2004Co-Authors: Iivari Kunttu, Leena Lepisto, Juhani Rauhamaa, Ari VisaAbstract:The shapes occurring in the images are important in the content-based image retrieval. We introduce a new Fourier-based Descriptor for the characterization of the shapes for retrieval purposes. This Descriptor combines the benefits of the wavelet transform and Fourier transform. This way the Fourier Descriptors can be presented in multiple scales, which improves the shape retrieval accuracy of the commonly used Fourier-Descriptors. The multiscale Fourier Descriptor is formed by applying the complex wavelet transforms to the boundary function of an object extracted from an image. After that, the Fourier transform is applied to the wavelet coefficients in multiple scales. This way the multiscale shape representation can be expressed in a rotation invariant form. The retrieval efficiency of this multiscale Fourier Descriptor is compared to an ordinary Fourier Descriptor and CSS-shape representation.
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ICPR (2) - Multiscale Fourier Descriptor for shape-based image retrieval
2004Co-Authors: Iivari Kunttu, Leena Lepisto, Juhani Rauhamaa, Ari VisaAbstract:The shapes occurring in the images are important in the content-based image retrieval. We introduce a new Fourier-based Descriptor for the characterization of the shapes for retrieval purposes. This Descriptor combines the benefits of the wavelet transform and Fourier transform. This way the Fourier Descriptors can be presented in multiple scales, which improves the shape retrieval accuracy of the commonly used Fourier-Descriptors. The multiscale Fourier Descriptor is formed by applying the complex wavelet transforms to the boundary function of an object extracted from an image. After that, the Fourier transform is applied to the wavelet coefficients in multiple scales. This way the multiscale shape representation can be expressed in a rotation invariant form. The retrieval efficiency of this multiscale Fourier Descriptor is compared to an ordinary Fourier Descriptor and CSS-shape representation.