Journal article Open Access

Automatic Moment-Based Texture Segmentation

Tudor Barbu


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{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Then, an automatic pixel classification approach is proposed. The feature vectors are clustered using an unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.</p>", 
  "license": "http://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "@type": "Person", 
      "name": "Tudor Barbu"
    }
  ], 
  "url": "https://zenodo.org/record/1089619", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2013-11-06", 
  "headline": "Automatic Moment-Based Texture Segmentation", 
  "version": "9996875", 
  "keywords": [
    "Image segmentation", 
    "moment-based texture analysis", 
    "automatic classification", 
    "validity indexes."
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.1089619", 
  "@id": "https://doi.org/10.5281/zenodo.1089619", 
  "@type": "ScholarlyArticle", 
  "name": "Automatic Moment-Based Texture Segmentation"
}
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