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Tytuł artykułu

Automated and effective content-based mammogram retrieval using wavelet based CS-LBP feature and self-organizing map

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper, automated, fast and effective content based-mammogram image retrieval system is proposed. The proposed pre-processing steps include automatic labelling-scratches suppression, automatic pectoral muscle removal and image enhancement. Further, for segmentation selective thresholds based seeded region growing algorithm is introduced. Furthermore, we apply 2-level discrete wavelet transform (DWT) on the segmented region and wavelet based centre symmetric-local binary pattern (WCS-LBP) features are extracted. Then, extracted features are fed to self-organizing map (SOM) which generates clusters of images, having similar visual content. SOM produces different clusters with their centres and query image features are matched with all cluster representatives to find closest cluster. Finally, images are retrieved from this closest cluster using Euclidean distance similarity measure. So, at the searching time the query image is searched only in small subset depending upon cluster size and is not compared with all the images in the database, reflects a superior response time with good retrieval performances. Descriptive experimental and empirical discussions confirm the effectiveness of this paper.
Twórcy
autor
  • Department of Computer Science & Engineering, Indian Institute of Technology (BHU), Varanasi 221005, India
  • Department of Computer Science & Engineering, Indian Institute of Technology (BHU), Varanasi 221005, India
Bibliografia
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Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2f93ba88-6997-4e93-a700-a1d427fb68f9
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