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A Quadtree-Based Unsupervised Segmentation Algorithm for Fruit Visual Inspection

  • Adolfo Martínez Usó
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2652)

Abstract

Many segmentation techniques are available in the literature and some of them have been widely used in different application problems. Most of these segmentation techniques were motivated by specific application purposes. In this article we present the preliminary results of an unsupervised segmentation algorithm through a multiresolution method using color information for fruit inspection tasks. The use of a Quadtree structure simplifies the combination of a multiresolution approach with the chosen strategy for the segmentation process and speeds up the whole procedure. The algorithm has been tested in fruit images in order to segment the different zones of the fruit surface. Due to the unsupervised nature of the procedure, it can adapt to the huge variability of color and shape of regions in fruit inspection applications.

Keywords

Image Segmentation Color Information Segmentation Process Color Region Fruit Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Adolfo Martínez Usó
    • 1
  1. 1.Filiberto Pla, Pedro García-SevillaUniversidad Jaume ICastellónSpain

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