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Optimized Multichannel Filter Bank with Flat Frequency Response for Texture Segmentation

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Τίτλος: Optimized Multichannel Filter Bank with Flat Frequency Response for Texture Segmentation
Συγγραφείς: Nezamoddin N. Kachouie, Javad Alirezaie
Έτος έκδοσης: 2022
Θεματικοί όροι: Biomedical signal processing, filter bank, extraction, gabor kernel, filter bank processing, Gabor, DCT, Multilayer Perceptron, Multilayer Perceptrons, Multilayer Perceptron Neural Networ., multilayer perceptron (MLP), competitive network, Texture segmentation, Pattern recognition systems, Image analysis -- Data processing
Περιγραφή: Previous approaches to texture analysis and segmentation use multichannel filtering by applying a set of filters in the frequency domain or a set of masks in the spatial domain. This paper presents two new texture segmentation algorithms based on multichannel filtering in conjunction with neural networks for feature extraction and segmentation. The features extracted by Gabor filters have been applied for image segmentation and analysis. Suitable choices of filter parameters and filter bank coverage in the frequency domain to optimize the filters are discussed. Here we introduce two methods to optimize Gabor filter bank. First, a Gabor filter bank with a flat response is implemented and the optimal feature dimension is extracted by competitive networks. Second, a subset of Gabor filter bank is selected to compose the best discriminative filters, so that each filter in this small set can discriminate a pair of textures in a given image. In both approaches, multilayer perceptrons are employed to segment the extracted features. The comparisons of segmentation results generated using the proposed methods and previous research using Gabor, discrete cosine transform (DCT), and Laws filters are presented. Finally, the segmentation results generated by applying the optimized filter banks to textured images are presented and discussed.
Τύπος εγγράφου: article in journal/newspaper
Γλώσσα: unknown
Relation: https://figshare.com/articles/journal_contribution/Optimized_Multichannel_Filter_Bank_with_Flat_Frequency_Response_for_Texture_Segmentation/21265788
DOI: 10.32920/21265788.v1
Διαθεσιμότητα: https://doi.org/10.32920/21265788.v1
https://figshare.com/articles/journal_contribution/Optimized_Multichannel_Filter_Bank_with_Flat_Frequency_Response_for_Texture_Segmentation/21265788
Rights: CC BY 4.0
Αριθμός Καταχώρησης: edsbas.D48DA5D9
Βάση Δεδομένων: BASE
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  – Url: https://doi.org/10.32920/21265788.v1#
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IllustrationInfo
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  Data: Optimized Multichannel Filter Bank with Flat Frequency Response for Texture Segmentation
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  Data: <searchLink fieldCode="AR" term="%22Nezamoddin+N%2E+Kachouie%22">Nezamoddin N. Kachouie</searchLink><br /><searchLink fieldCode="AR" term="%22Javad+Alirezaie%22">Javad Alirezaie</searchLink>
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  Data: 2022
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  Data: <searchLink fieldCode="DE" term="%22Biomedical+signal+processing%22">Biomedical signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22filter+bank%22">filter bank</searchLink><br /><searchLink fieldCode="DE" term="%22extraction%22">extraction</searchLink><br /><searchLink fieldCode="DE" term="%22gabor+kernel%22">gabor kernel</searchLink><br /><searchLink fieldCode="DE" term="%22filter+bank+processing%22">filter bank processing</searchLink><br /><searchLink fieldCode="DE" term="%22Gabor%22">Gabor</searchLink><br /><searchLink fieldCode="DE" term="%22DCT%22">DCT</searchLink><br /><searchLink fieldCode="DE" term="%22Multilayer+Perceptron%22">Multilayer Perceptron</searchLink><br /><searchLink fieldCode="DE" term="%22Multilayer+Perceptrons%22">Multilayer Perceptrons</searchLink><br /><searchLink fieldCode="DE" term="%22Multilayer+Perceptron+Neural+Networ%2E%22">Multilayer Perceptron Neural Networ.</searchLink><br /><searchLink fieldCode="DE" term="%22multilayer+perceptron+%28MLP%29%22">multilayer perceptron (MLP)</searchLink><br /><searchLink fieldCode="DE" term="%22competitive+network%22">competitive network</searchLink><br /><searchLink fieldCode="DE" term="%22Texture+segmentation%22">Texture segmentation</searchLink><br /><searchLink fieldCode="DE" term="%22Pattern+recognition+systems%22">Pattern recognition systems</searchLink><br /><searchLink fieldCode="DE" term="%22Image+analysis+--+Data+processing%22">Image analysis -- Data processing</searchLink>
– Name: Abstract
  Label: Description
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  Data: Previous approaches to texture analysis and segmentation use multichannel filtering by applying a set of filters in the frequency domain or a set of masks in the spatial domain. This paper presents two new texture segmentation algorithms based on multichannel filtering in conjunction with neural networks for feature extraction and segmentation. The features extracted by Gabor filters have been applied for image segmentation and analysis. Suitable choices of filter parameters and filter bank coverage in the frequency domain to optimize the filters are discussed. Here we introduce two methods to optimize Gabor filter bank. First, a Gabor filter bank with a flat response is implemented and the optimal feature dimension is extracted by competitive networks. Second, a subset of Gabor filter bank is selected to compose the best discriminative filters, so that each filter in this small set can discriminate a pair of textures in a given image. In both approaches, multilayer perceptrons are employed to segment the extracted features. The comparisons of segmentation results generated using the proposed methods and previous research using Gabor, discrete cosine transform (DCT), and Laws filters are presented. Finally, the segmentation results generated by applying the optimized filter banks to textured images are presented and discussed.
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  Data: https://figshare.com/articles/journal_contribution/Optimized_Multichannel_Filter_Bank_with_Flat_Frequency_Response_for_Texture_Segmentation/21265788
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  Data: 10.32920/21265788.v1
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  Data: https://doi.org/10.32920/21265788.v1<br />https://figshare.com/articles/journal_contribution/Optimized_Multichannel_Filter_Bank_with_Flat_Frequency_Response_for_Texture_Segmentation/21265788
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        Value: 10.32920/21265788.v1
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    Subjects:
      – SubjectFull: Biomedical signal processing
        Type: general
      – SubjectFull: filter bank
        Type: general
      – SubjectFull: extraction
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      – SubjectFull: filter bank processing
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      – SubjectFull: Texture segmentation
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      – SubjectFull: Pattern recognition systems
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      – SubjectFull: Image analysis -- Data processing
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      – TitleFull: Optimized Multichannel Filter Bank with Flat Frequency Response for Texture Segmentation
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