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    Adriana Bodnarova

    Gabor filters have proved to be an effective segmentation and flaw detection tool. This study addresses the issue of an optimal 2-D Gabor filter design for automatically detecting defects in homogeneously textured woven fabrics. The... more
    Gabor filters have proved to be an effective segmentation and flaw detection tool. This study addresses the issue of an optimal 2-D Gabor filter design for automatically detecting defects in homogeneously textured woven fabrics. The parameters of these filters are derived through an optimisation process performing the minimisation of a Fisher cost function. By constraining some of the Gabor filter parameters to specific values the aim is to optimise the filter to detect a certain type of flaw as it appears in a particular textile background. To account for the potentially large variety of flaw types, the optimal parameters for multiple sets of constraints are computed. The detection outcomes from each set of optimal filters are combined to produce a final classification result. Successful detection results (with low false alarm rates) suggest that this optimal Gabor filter approach is a promising method for automated detection of flaws in homogenous textiles
    This study presents a new automatic and fast approach to design optimised Gabor filters for textile flaw detection applications. The defect detection problem is solved by using a semi-supervised approach. The aim is to automatically... more
    This study presents a new automatic and fast approach to design optimised Gabor filters for textile flaw detection applications. The defect detection problem is solved by using a semi-supervised approach. The aim is to automatically discriminate between “known” nondefective background textures and “unknown” defective textures. The parameters of the optimal 2D Gabor filters are derived by constrained minimisation of a
    ABSTRACT This work is a part of ongoing research in the area of automatic visual inspection systems for real-time detection of fabric defects. The study aims to extend and evaluate the application of the joint space/spatial-frequency... more
    ABSTRACT This work is a part of ongoing research in the area of automatic visual inspection systems for real-time detection of fabric defects. The study aims to extend and evaluate the application of the joint space/spatial-frequency approach represented by the use of Gabor elementary functions for inspecting intricate jacquard patterns. It assesses the utility of multiresolution properties of Gabor-filters and the need for adaptive selection and integration of appropriate resolution levels of the image pyramid. The choice of the appropriate levels takes into consideration characteristics of the potential defects.
    The task of detecting flaws in woven textiles can be formulated as the problem of segmenting a “known” non-defective texture from an “unknown” defective texture. In order to discriminate defective texture pixels from non-defective texture... more
    The task of detecting flaws in woven textiles can be formulated as the problem of segmenting a “known” non-defective texture from an “unknown” defective texture. In order to discriminate defective texture pixels from non-defective texture pixels, optimal 2-D Gabor filters are designed such that, when applied to non-defective texture, the filter response maximises a Fisher cost function. A pixel of
    ABSTRACT This article dealth with a complex problem of textile quality control by the means of computer vision using advanced digital signal and image processing tools. An investigation into a computer vision solution to quality... more
    ABSTRACT This article dealth with a complex problem of textile quality control by the means of computer vision using advanced digital signal and image processing tools. An investigation into a computer vision solution to quality inspection of textiles suggested a texture analysis approach. Since each texture analysis method presents a different potential for analysis of textured textile images, a large number of standard approaches from this category was examined. By considering their advantages and potential for successful flaw detection performance in homogeneous and jacquard textiles, six standard texture analysis techniques were identified for further investigation. A comprehensive examination and evaluation of these chosen techniques resulted. Normalised cross-correlation and SCLC approaches were identified as suitable candidates for real-time flaw detection in textiles with homogeneous structure.Inspection of jacquard textiles, however, presents a problem of greater complexity, the solution to which has not as yet been documented in the literature. To address this problem, a need for the application of a comprehensive cojoint spatial-spatial frequency approach was identified. A Gabor filter approach was chosen as a suitable representative of this class of techniques. This research then successfully applied optimised 2-D Gabor filters to the textile flaw detection problem and provided a further support of their suitability for this task.A novel optimised 2-D Gabor algorithm presented in this study is an automatic solution which is adaptable to detect a large variety of textile flaw types, both structural and tonal.
    This paper examines the problem of quality control and defect identification in woven textile fabrics by introducing an improved method for texture description. The approach is based on spatial gray level dependence methodology and... more
    This paper examines the problem of quality control and defect identification in woven textile fabrics by introducing an improved method for texture description. The approach is based on spatial gray level dependence methodology and addresses the issue of optimal parameter selection for deriving the maximum textural information. We introduce the use of the χ2 significance test on elemental feature matrices
    Gabor filters have proved to be an effective segmentation and flaw detection tool. This study addresses the issue of an optimal 2-D Gabor filter design for automatically detecting defects in homogeneously textured woven fabrics. The... more
    Gabor filters have proved to be an effective segmentation and flaw detection tool. This study addresses the issue of an optimal 2-D Gabor filter design for automatically detecting defects in homogeneously textured woven fabrics. The parameters of these filters are derived through an optimisation process performing the minimisation of a Fisher cost function. By constraining some of the Gabor filter parameters to specific values the aim is to optimise the filter to detect a certain type of flaw as it appears in a particular textile background. To account for the potentially large variety of flaw types, the optimal parameters for multiple sets of constraints are computed. The detection outcomes from each set of optimal filters are combined to produce a final classification result. Successful detection results (with low false alarm rates) suggest that this optimal Gabor filter approach is a promising method for automated detection of flaws in homogenous textiles
    ABSTRACT This work is a part of ongoing research in the area of automatic visual inspection systems for real-time detection of fabric defects. The study aims to extend and evaluate the application of the joint space/spatial-frequency... more
    ABSTRACT This work is a part of ongoing research in the area of automatic visual inspection systems for real-time detection of fabric defects. The study aims to extend and evaluate the application of the joint space/spatial-frequency approach represented by the use of Gabor elementary functions for inspecting intricate jacquard patterns. It assesses the utility of multiresolution properties of Gabor-filters and the need for adaptive selection and integration of appropriate resolution levels of the image pyramid. The choice of the appropriate levels takes into consideration characteristics of the potential defects.
    This paper provides a synthesis of a number of textile flaw detection techniques. The review highlights the issues pertaining to textile visual quality inspection and outlines its objectives and problems. Furthermore it looks at the... more
    This paper provides a synthesis of a number of textile flaw detection techniques. The review highlights the issues pertaining to textile visual quality inspection and outlines its objectives and problems. Furthermore it looks at the general taxonomy of texture analysis approaches and their suitability for the task of textile quality inspection. The paper also details and provides a comparison of
    ABSTRACT This article dealth with a complex problem of textile quality control by the means of computer vision using advanced digital signal and image processing tools. An investigation into a computer vision solution to quality... more
    ABSTRACT This article dealth with a complex problem of textile quality control by the means of computer vision using advanced digital signal and image processing tools. An investigation into a computer vision solution to quality inspection of textiles suggested a texture analysis approach. Since each texture analysis method presents a different potential for analysis of textured textile images, a large number of standard approaches from this category was examined. By considering their advantages and potential for successful flaw detection performance in homogeneous and jacquard textiles, six standard texture analysis techniques were identified for further investigation. A comprehensive examination and evaluation of these chosen techniques resulted. Normalised cross-correlation and SCLC approaches were identified as suitable candidates for real-time flaw detection in textiles with homogeneous structure.Inspection of jacquard textiles, however, presents a problem of greater complexity, the solution to which has not as yet been documented in the literature. To address this problem, a need for the application of a comprehensive cojoint spatial-spatial frequency approach was identified. A Gabor filter approach was chosen as a suitable representative of this class of techniques. This research then successfully applied optimised 2-D Gabor filters to the textile flaw detection problem and provided a further support of their suitability for this task.A novel optimised 2-D Gabor algorithm presented in this study is an automatic solution which is adaptable to detect a large variety of textile flaw types, both structural and tonal.
    This study presents a new automatic and fast approach to design optimised Gabor filters for textile flaw detection applications. The defect detection problem is solved by using a semi-supervised approach. The aim is to automatically... more
    This study presents a new automatic and fast approach to design optimised Gabor filters for textile flaw detection applications. The defect detection problem is solved by using a semi-supervised approach. The aim is to automatically discriminate between “known” nondefective background textures and “unknown” defective textures. The parameters of the optimal 2D Gabor filters are derived by constrained minimisation of a
    The task of detecting flaws in woven textiles can be formulated as the problem of segmenting a “known” non-defective texture from an “unknown” defective texture. In order to discriminate defective texture pixels from non-defective texture... more
    The task of detecting flaws in woven textiles can be formulated as the problem of segmenting a “known” non-defective texture from an “unknown” defective texture. In order to discriminate defective texture pixels from non-defective texture pixels, optimal 2-D Gabor filters are designed such that, when applied to non-defective texture, the filter response maximises a Fisher cost function. A pixel of